{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Chapter 3 Code - Python 3 version\n",
    "\n",
    "### classifierPerformance_RocksVMines.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of xTrain array (138, 60)\n",
      "Shape of yTrain array (138,)\n",
      "Shape of xTest array (70, 60)\n",
      "Shape of yTest array (70,)\n",
      "Some values predicted by model [-0.10240253  0.42090698  0.38593034  0.36094537  0.31520494] [ 1.11094176  1.12242751  0.77626699  1.02016858  0.66338081]\n",
      "tp = 68.0\tfn = 6.0\n",
      "fp = 7.0\ttn = 57.0\n",
      "\n",
      "tp = 28.0\tfn = 9.0\n",
      "fp = 9.0\ttn = 24.0\n",
      "\n",
      "AUC for in-sample ROC curve: 0.979519\n"
     ]
    },
    {
     "data": {
      "image/png": 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nYHwcyw0C/qWqlXAO1Efdcg2dgdru+EigeyLbbw1sE5EA\nYCbQWVXL41QyGCwiBYCHgbKqWgEY5bmwqs4FNuL88q+kqpc9Js8F2nsMdwa+SGaczXDKdER7SVWD\ngQpAPRGpoKrjcWr5NFDVBm4pj5eBh9x9uREYnsh2TCaXJkt4mEzvsnuw9JQNmOC2yUfi1C2KbQ3w\nkogUBr5W1X0i0gioCmxwy5vkxEk6cflMRC4Dv+GUob4fOKSqe93ps4DHgQk4z7qYJiLfAV6XNFfV\nUyJy0K2zs8/dxmp3vUmJMzdOuQrPJ5R1EpGBOH/XBXEe0LM11rI13fGr3e1kx9lvxsTLEoVJL4YB\nfwAVcc6Eb3gokap+LiLrgJbAYhHpj1NWeZaqvuDFNrp7FhAUkTifb+LWFqqOU2SuCzAUaJiEz/IF\n0AnYDcxTVRXnqO11nDhPcXsLmAi0F5ESwEigmqqeEZGZOIXvYhPgf6raNQnxmkzOmp5MepEPOO4+\nP6AHzq/p64hISeCg29yyAKcJ5kego4jc6c5TQLx/pvhuoLiIlHKHewAr3Db9fKq6CKejOK4rj87j\nlD2Py9dAO5xnJHzhjktSnKoajtOEVNNttroVuAicFZG7gObxxLIWqB39mUQkl4jEdXZmTAxLFCa9\n+BDoJSJrcZqdLsYxT2dgu4iEAGVwHvm4E+eAukREtgL/w2mWSZSqhuFU1/xSRLYBUcAknIPut+76\nVuCc7cQ2E5gU3Zkda71ngJ1AMVVd745Lcpxu38d7wEhV3YLzfOwdwAyc5qxoU4DvRWS5qp7CuSLr\nv+521uLsK2PiZdVjjTHGJMjOKIwxxiTIEoUxxpgEWaIwxhiTIEsUxhhjEmSJwhhjTIIsURhjjEmQ\nJQpjjDEJ+n+IU8gMN4C8NAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3266405860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AUC for out-of-sample ROC curve: 0.848485\n"
     ]
    },
    {
     "data": {
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Acw+KYsBEj/EngS2+DMqYjOa3337jjz/+4PPPP6djx46BDseYdJVsolDVA8AB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\nOF5ui9eA/MAc93z+IVXtELCgfcTLbZE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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3235937828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "__author__ = 'mike-bowles'\n",
    "#use scikit learn package to perform linear regression\n",
    "#read in the rocks versus mines data set from uci.edu data repository\n",
    "import urllib.request, urllib.error, urllib.parse\n",
    "import numpy\n",
    "import random\n",
    "from sklearn import datasets, linear_model\n",
    "from sklearn.metrics import roc_curve, auc\n",
    "import pylab as pl\n",
    "\n",
    "\n",
    "def confusionMatrix(predicted, actual, threshold):\n",
    "    if len(predicted) != len(actual): return -1\n",
    "    tp = 0.0\n",
    "    fp = 0.0\n",
    "    tn = 0.0\n",
    "    fn = 0.0\n",
    "    for i in range(len(actual)):\n",
    "        if actual[i] > 0.5: #labels that are 1.0  (positive examples)\n",
    "            if predicted[i] > threshold:\n",
    "                tp += 1.0 #correctly predicted positive\n",
    "            else:\n",
    "                fn += 1.0 #incorrectly predicted negative\n",
    "        else:              #labels that are 0.0 (negative examples)\n",
    "            if predicted[i] < threshold:\n",
    "                tn += 1.0 #correctly predicted negative\n",
    "            else:\n",
    "                fp += 1.0 #incorrectly predicted positive\n",
    "    rtn = [tp, fn, fp, tn]\n",
    "    return rtn\n",
    "\n",
    "\n",
    "#read data from uci data repository\n",
    "target_url = \"https://archive.ics.uci.edu/ml/machine-learning-databases/undocumented/connectionist-bench/sonar/sonar.all-data\"\n",
    "data = urllib.request.urlopen(target_url)\n",
    "\n",
    "#arrange data into list for labels and list of lists for attributes\n",
    "xList = []\n",
    "labels = []\n",
    "for line in data:\n",
    "    #split on comma\n",
    "    row = line.strip().decode().split(\",\")\n",
    "    #assign label 1.0 for \"M\" and 0.0 for \"R\"\n",
    "    if(row[-1] == 'M'):\n",
    "        labels.append(1.0)\n",
    "    else:\n",
    "        labels.append(0.0)\n",
    "    #remove label from row\n",
    "    row.pop()\n",
    "    #convert row to floats\n",
    "    floatRow = [float(num) for num in row]\n",
    "    xList.append(floatRow)\n",
    "\n",
    "#divide attribute matrix and label vector into training(2/3 of data) and test sets (1/3 of data)\n",
    "indices = range(len(xList))\n",
    "xListTest = [xList[i] for i in indices if i%3 == 0 ]\n",
    "xListTrain = [xList[i] for i in indices if i%3 != 0 ]\n",
    "labelsTest = [labels[i] for i in indices if i%3 == 0]\n",
    "labelsTrain = [labels[i] for i in indices if i%3 != 0]\n",
    "\n",
    "#form list of list input into numpy arrays to match input class for scikit-learn linear model\n",
    "xTrain = numpy.array(xListTrain); yTrain = numpy.array(labelsTrain); xTest = numpy.array(xListTest); yTest = numpy.array(labelsTest)\n",
    "\n",
    "#check shapes to see what they look like\n",
    "print(\"Shape of xTrain array\", xTrain.shape)\n",
    "print(\"Shape of yTrain array\", yTrain.shape)\n",
    "print(\"Shape of xTest array\", xTest.shape)\n",
    "print(\"Shape of yTest array\", yTest.shape)\n",
    "\n",
    "#train linear regression model\n",
    "rocksVMinesModel = linear_model.LinearRegression()\n",
    "rocksVMinesModel.fit(xTrain,yTrain)\n",
    "\n",
    "#generate predictions on in-sample error\n",
    "trainingPredictions = rocksVMinesModel.predict(xTrain)\n",
    "print(\"Some values predicted by model\", trainingPredictions[0:5], trainingPredictions[-6:-1])\n",
    "\n",
    "#generate confusion matrix for predictions on training set (in-sample\n",
    "confusionMatTrain = confusionMatrix(trainingPredictions, yTrain, 0.5)\n",
    "#pick threshold value and generate confusion matrix entries\n",
    "tp = confusionMatTrain[0]; fn = confusionMatTrain[1]; fp = confusionMatTrain[2]; tn = confusionMatTrain[3]\n",
    "\n",
    "print(\"tp = \" + str(tp) + \"\\tfn = \" + str(fn) + \"\\n\" + \"fp = \" + str(fp) + \"\\ttn = \" + str(tn) + '\\n')\n",
    "\n",
    "#generate predictions on out-of-sample data\n",
    "testPredictions = rocksVMinesModel.predict(xTest)\n",
    "\n",
    "#generate confusion matrix from predictions on out-of-sample data\n",
    "conMatTest = confusionMatrix(testPredictions, yTest, 0.5)\n",
    "#pick threshold value and generate confusion matrix entries\n",
    "tp = conMatTest[0]; fn = conMatTest[1]; fp = conMatTest[2]; tn = conMatTest[3]\n",
    "print(\"tp = \" + str(tp) + \"\\tfn = \" + str(fn) + \"\\n\" + \"fp = \" + str(fp) + \"\\ttn = \" + str(tn) + '\\n')\n",
    "\n",
    "#generate ROC curve for in-sample\n",
    "\n",
    "fpr, tpr, thresholds = roc_curve(yTrain,trainingPredictions)\n",
    "roc_auc = auc(fpr, tpr)\n",
    "print( 'AUC for in-sample ROC curve: %f' % roc_auc)\n",
    "\n",
    "# Plot ROC curve\n",
    "pl.clf()\n",
    "pl.plot(fpr, tpr, label='ROC curve (area = %0.2f)' % roc_auc)\n",
    "pl.plot([0, 1], [0, 1], 'k--')\n",
    "pl.xlim([0.0, 1.0])\n",
    "pl.ylim([0.0, 1.0])\n",
    "pl.xlabel('False Positive Rate')\n",
    "pl.ylabel('True Positive Rate')\n",
    "pl.title('In sample ROC rocks versus mines')\n",
    "pl.legend(loc=\"lower right\")\n",
    "pl.show()\n",
    "\n",
    "#generate ROC curve for out-of-sample\n",
    "fpr, tpr, thresholds = roc_curve(yTest,testPredictions)\n",
    "roc_auc = auc(fpr, tpr)\n",
    "print( 'AUC for out-of-sample ROC curve: %f' % roc_auc)\n",
    "\n",
    "# Plot ROC curve\n",
    "pl.clf()\n",
    "pl.plot(fpr, tpr, label='ROC curve (area = %0.2f)' % roc_auc)\n",
    "pl.plot([0, 1], [0, 1], 'k--')\n",
    "pl.xlim([0.0, 1.0])\n",
    "pl.ylim([0.0, 1.0])\n",
    "pl.xlabel('False Positive Rate')\n",
    "pl.ylabel('True Positive Rate')\n",
    "pl.title('Out-of-sample ROC rocks versus mines')\n",
    "pl.legend(loc=\"lower right\")\n",
    "pl.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### classifierRidgeRocksVMines.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AUC             alpha\n",
      "0.841113841114 999.9999999999999\n",
      "0.864045864046 99.99999999999999\n",
      "0.907452907453 10.0\n",
      "0.9180999181 1.0\n",
      "0.882882882883 0.1\n",
      "0.861588861589 0.010000000000000002\n",
      "0.851760851761 0.0010000000000000002\n",
      "0.850941850942 0.00010000000000000002\n",
      "0.849303849304 1.0000000000000003e-05\n"
     ]
    },
    {
     "data": {
      "image/png": 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4w7Fioaoe4FZgHrAG71lPq0Rkhohc7Bv2C+DHIpKDdw/iBj3y034mkKeq1owY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\n1CcbmJjRhXP6dXQ7jjHGuMq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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f32359374a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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Czsw3qJSybqtEIWfnmwCcmW8w3Bdxdr5JrZVQayXFci2arjXxvOSWwoDZWmvJ\nMp+ZbxAFtmwdrLWMx07PM9eIqbWSItdsrUmp7dt3KTKaccrkbJZtcTonpmsrLv+Dx6YY7isV/bOY\nbXH6M/Vs38LkbIP+cshs/kG8uCxn5htF0WtfRwBn55tUopBKKaTWSlbN0NmHa/XdEyfnGO6LqJRC\nznasu8U+GO6LeOLk3IrPX2l+Ilull0VhpW/8nWNV3bTBzO4wsyNmdmRycvK8wtRayZLNeoBmnBAF\nRitJCQMIzYiTpc+LAqMZJ6RpWrRfTRQYSerFB183GTqVQis+1NvbNuPsm3icZDkBwsCIkxSAOMmG\ni+IkJU2dNPViuRbFSYrlqzfIs7Yvc5xAYE4rWX1IsXMZa61s3aT+Qq44dYK2+QZmpA5x3m5xOs04\nXXH555sxpdCWrO/25U4SKAXQShJKeR54of/iJHthufuSdbS4DsLACAPyPl05Q2cfrtV39WZMOQwI\nA2glS6e32AflMKDejFd8/krzE9kqvSwKE8D+tvv7gOdWa2NmETACnO2ckLvf5e7j7j6+c+fO8wpT\nLYXLPuzKUUicOqUwIEkhcadz1CROnXIUEgRB0X41cZp9CFVXGRteKUOnVuJUS+GytuUoIE6zfEm+\nHyjJh2gAohCaSUoUBtmYfWDFci2KwgDP63CaZ21f5iiE1G3NwtW5jNVStm4CeyFXFBhp23xTdwKD\nKG+3OJ32sfz25R8oR7QSX7K+25c7DKGVQikMaeV54IX+i8Lsm4WZLVlHi+sgSZ0kJe/TlTN09uFa\nfddXjmgmKUlKsT9q0WIfNJOUvlW2Mlean8hW6WVRuB84ZGZXmlkZuA043NHmMPCj+e23A3/lPdrz\nfXBsgJn60vHePSN9LDRjtg9UaLQSGq2UHQOVJW0WmjF7RvoYrERcNlJlYZVvewALjYSBSsTBsYGu\nM3Saqbc4ODawrO3ekSoLjYQdAxUarewTtxEnbB/IjlrZMVBhph6zfaBcFJXF5Vo0Ui1j+dptJSlD\n1dKSZd4xUCFOfdk6WGsZD44NMFiJqJbCItdQtUyr7Rt4K84KwM6hcvHht9BI2DtSXXH5bzg4yky9\nVfTPYrbF6Q/3lVhoJOwcqrDQTBiqZsM6i8uyY6CCWbaTuX0dAWwfKNOIExr5YaGrZejsw7X67tDu\nQWbqMY1WwvaOdbfYBzP1mEO7B1d8/krzE9kqPSsK+T6C9wF3A48CH3f3h83sg2Z2S97sd4EdZnYU\neD/wgV7l2TfaTxiw5EN951CFIIBqKSB2J0mckf4Xxo3rcUIQwGAlYtdwHy/fPUQrTal3jjGRHZnT\nSlN2DpXZN9rfdYZ2C82YMMi6NrxkAAAI5klEQVTadbbdOVghCIy+UoCRDbGYwbY8b6UcEAUQGGzr\nLzPSX6JaCrDAaOVHTo0Nlukvhcw1W8WHpmHFMlvgDPWVGBsqd72M+0b72TXcR7WSbck045TBcojl\nwzZxkpK4UykZl49W2TYQMV1vEgTGzsHlBTgM4IYDo4T5eg+CrB9G+ksY2ZBTOTJCg4FyQGhQCbPH\nF5elUg4YqkSEoRGnabGOIFtfcerU4oTR/vKqGTr7cK2+u3r3EE42zW3VpfsdtlVL1PJDhq/ePbRm\nn4tcDHp6nkIv6DwFnaeg8xRENm7Lz1PolQspCqAzmnVGs85olm9NKgoiIlK4GE5eExGRS4yKgoiI\nFFQURESkoKIgIiIFFQURESmoKIiISEFFQURECpfceQpmNgk8vdU5gDHg9FaH2ADl7b1LLbPy9tbF\nlvcKd1/3iqKXXFG4WJjZkW5OBLlYKG/vXWqZlbe3LrW8izR8JCIiBRUFEREpqCicv7u2OsAGKW/v\nXWqZlbe3LrW8gPYpiIhIG20piIhIQUVhHWZ2s5k9bmZHzWzZL8OZWcXM/jj/+5fM7ODmp1ySZ728\n7zezR8zsITP7jJldsRU52/Ksmbet3dvNzM1sS4/m6Cavmf1gvo4fNrM/2uyMK+RZ7zVxwMw+a2Zf\nzl8Xb9uKnHmW3zOzU2b29VX+bmb2G/myPGRmN2x2xhUyrZf5h/KsD5nZPWb27ZudcUPcXf9W+QeE\nwJPAy4Ay8FXg2o42PwH8l/z2bcAfX+R5Xw/057d//GLPm7cbAj4P3AeMX8x5gUPAl4HR/P6urcq7\ngcx3AT+e374WOLaFeb8buAH4+ip/fxvwvwADvhP40lau3y4zv67t9fDWiyHzWv+0pbC2m4Cj7v6U\nuzeBjwG3drS5FfhwfvtPgDeamW1ixnbr5nX3z7r7Qn73PmDfJmds1836BfhF4FeA+maGW0E3ed8D\n3OnuUwDufmqTM3bqJrMDw/ntEeC5Tcy3NIj754GzazS5FfiIZ+4DtpnZ3s1Jt7L1Mrv7PYuvB7b+\nPbcuFYW1XQ4cb7s/kT+2Yht3j4FpYMempFuum7zt3k32rWurrJvXzK4H9rv7X2xmsFV0s36vBq42\nsy+a2X1mdvOmpVtZN5l/AXinmU0AnwJ+cnOinZeNvsYvNlv9nltXtNUBLnIrfePvPFyrmzabpess\nZvZOYBz4np4mWtuaec0sAH4NeNdmBVpHN+s3IhtC+l6yb4RfMLPr3P1cj7OtppvMtwN/4O7/wcz+\nBvCHeea09/E27GJ6v22Imb2erCj8za3OshZtKaxtAtjfdn8fyzetizZmFpFtfq+1+dtL3eTFzN4E\n/Bxwi7s3NinbStbLOwRcB3zOzI6RjSEf3sKdzd2+Hv6Hu7fc/ZvA42RFYqt0k/ndwMcB3P1eoI/s\nuj0Xo65e4xcbM3s18DvAre5+ZqvzrEVFYW33A4fM7EozK5PtSD7c0eYw8KP57bcDf+X5HqUtsG7e\nfDjmQ2QFYavHu9fM6+7T7j7m7gfd/SDZeOwt7n5ka+J29Xr472Q78zGzMbLhpKc2NeVS3WR+Bngj\ngJm9kqwoTG5qyu4dBn4kPwrpO4Fpdz+x1aHWYmYHgD8Fftjdv7HVeda11Xu6L/Z/ZEc7fIPsCI6f\nyx/7INmHE2RvoE8AR4H/B7zsIs/7f4CTwFfyf4cv5rwdbT/HFh591OX6NeA/Ao8AXwNu28q8XWa+\nFvgi2ZFJXwHesoVZPwqcAFpkWwXvBt4LvLdt/d6ZL8vXtvr10GXm3wGm2t5zR7Y681r/dEaziIgU\nNHwkIiIFFQURESmoKIiISEFFQURECioKIiJSUFGQS46ZJWb2FTP7upl9wsz6L2Ba32tmf5HfvmWd\nK7VuM7OfOI95/IKZ/bMV5ntvx2ORmZ1c61o+K01L5MWkoiCXopq7v8bdrwOaZMeEF/ITmzb82nb3\nw+7+y2s02UZ2VdwXw+eBfR2XWn8T2ZU2L+qTseSlTUVBLnVfAF5uZgfN7FEz+03gQWC/mb3FzO41\nswfzLYpBKH5f4DEz+2vg7y1OyMzeZWb/Ob+928z+zMy+mv97HfDLwFX5Vsqv5u1+1szuz6+V/6/b\npvVz+W8Y/B/gFZ2hPbuu0CeAd7Q9fBvZiVCY2Xvy6X7VzD650taQmX1u8ZIfZjaWXwoEMwvN7Ffb\ncv2j81+98q1GRUEuWfm1pt5KdmYrZB++H3H364F54F8Cb3L3G4AjwPvNrA/4beDvAn8L2LPK5H8D\n+L/u/u1k18p/GPgA8GS+lfKzZvYWsusa3QS8BrjRzL7bzG4k+4C/nqzovHaVeXw0b4eZVcjOPP5k\n/rc/dffX5vN/lOws2W69m+zyD6/N5/0eM7tyA8+Xb2G6Sqpciqpm9pX89heA3wUuA5727Br7kF08\n71rgi/nPW5SBe4FrgG+6+xMAZvZfgTtWmMcbgB8BcPcEmDaz0Y42b8n/fTm/P0hWJIaAP/P8dyvM\nrPNaQ+TTvd/MBs3sFcArgfv8hevuX2dmv0Q2ZDUI3L3uWlma69Vm9vb8/kie65sbmIZ8i1JRkEtR\nzd1f0/5A/sE/3/4Q8Gl3v72j3Wt48S61bMC/c/cPdczjpzYwj4+RbS28knzoKPcHwPe5+1fN7F1k\nl+LuFPPC1n5fR66fdPeNFBIRQMNH8tJ1H/BdZvZyADPrN7OrgceAK83sqrzd7as8/zNkP1e6OEY/\nDMySbQUsuhv4sbZ9FZeb2S6yncjfb2ZVMxsiG6pazUeBd5JtmbRvUQwBJ8ysBPzQKs89BtyY3357\n2+N3Az+ePxczu9rMBtbIIFJQUZCXJHefJPtxno+a2UNkReIad6+TDRf9z3xH89OrTOKfAq83s68B\nDwCv8uw6+F/MD4X9VXf/38AfAffm7f4EGHL3B4E/Jrsi5ifJhrhWy/kIsEB2yfX2LZ1/BXwJ+DRZ\nIVvJvyf78L+Hpb9/8DtkV2l90LIfk/8QGhWQLukqqSIiUtCWgoiIFFQURESkoKIgIiIFFQURESmo\nKIiISEFFQURECioKIiJSUFEQEZHC/wfIeOgTu3spJgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f32359374e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "__author__ = 'mike-bowles'\n",
    "import urllib.request, urllib.error, urllib.parse\n",
    "import numpy\n",
    "from sklearn import datasets, linear_model\n",
    "from sklearn.metrics import roc_curve, auc\n",
    "import pylab as plt\n",
    "\n",
    "#read data from uci data repository\n",
    "target_url = \"https://archive.ics.uci.edu/ml/machine-learning-databases/undocumented/connectionist-bench/sonar/sonar.all-data\"\n",
    "data = urllib.request.urlopen(target_url)\n",
    "\n",
    "#arrange data into list for labels and list of lists for attributes\n",
    "xList = []\n",
    "labels = []\n",
    "for line in data:\n",
    "    #split on comma\n",
    "    row = line.strip().decode().split(\",\")\n",
    "    #assign label 1.0 for \"M\" and 0.0 for \"R\"\n",
    "    if(row[-1] == 'M'):\n",
    "        labels.append(1.0)\n",
    "    else:\n",
    "        labels.append(0.0)\n",
    "        #remove lable from row\n",
    "    row.pop()\n",
    "    #convert row to floats\n",
    "    floatRow = [float(num) for num in row]\n",
    "    xList.append(floatRow)\n",
    "\n",
    "#divide attribute matrix and label vector into training(2/3 of data) and test sets (1/3 of data)\n",
    "indices = range(len(xList))\n",
    "xListTest = [xList[i] for i in indices if i%3 == 0 ]\n",
    "xListTrain = [xList[i] for i in indices if i%3 != 0 ]\n",
    "labelsTest = [labels[i] for i in indices if i%3 == 0]\n",
    "labelsTrain = [labels[i] for i in indices if i%3 != 0]\n",
    "\n",
    "#form list of list input into numpy arrays to match input class for scikit-learn linear model\n",
    "xTrain = numpy.array(xListTrain); yTrain = numpy.array(labelsTrain); xTest = numpy.array(xListTest); yTest = numpy.array(labelsTest)\n",
    "\n",
    "alphaList = [0.1**i for i in [-3, -2, -1, 0,1, 2, 3, 4, 5]]\n",
    "\n",
    "aucList = []\n",
    "for alph in alphaList:\n",
    "    rocksVMinesRidgeModel = linear_model.Ridge(alpha=alph)\n",
    "    rocksVMinesRidgeModel.fit(xTrain, yTrain)\n",
    "    fpr, tpr, thresholds = roc_curve(yTest,rocksVMinesRidgeModel.predict(xTest))\n",
    "    roc_auc = auc(fpr, tpr)\n",
    "    aucList.append(roc_auc)\n",
    "\n",
    "    \n",
    "print(\"AUC             alpha\")\n",
    "for i in range(len(aucList)):\n",
    "    print(aucList[i], alphaList[i])\n",
    "\n",
    "#plot auc values versus alpha values\n",
    "x = [-3, -2, -1, 0,1, 2, 3, 4, 5]\n",
    "plt.plot(x, aucList)\n",
    "plt.xlabel('-log(alpha)')\n",
    "plt.ylabel('AUC')\n",
    "plt.show()\n",
    "\n",
    "#visualize the performance of the best classifier\n",
    "indexBest = aucList.index(max(aucList))\n",
    "alph = alphaList[indexBest]\n",
    "rocksVMinesRidgeModel = linear_model.Ridge(alpha=alph)\n",
    "rocksVMinesRidgeModel.fit(xTrain, yTrain)\n",
    "\n",
    "#scatter plot of actual vs predicted\n",
    "plt.scatter(rocksVMinesRidgeModel.predict(xTest), yTest, s=100, alpha=0.25)\n",
    "plt.xlabel(\"Predicted Value\")\n",
    "plt.ylabel(\"Actual Value\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### fwdStepwiseWine.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Out of sample error versus attribute set size\n",
      "[0.72342592551162777, 0.68609931528371959, 0.67343650334202776, 0.66770332138977961, 0.6622558568522271, 0.65900047541546247, 0.65727172061430761, 0.65709058062076997, 0.65699930964461373, 0.65758189400434741, 0.65739098690113373]\n",
      "\n",
      "Best attribute indices\n",
      "[10, 1, 9, 4, 6, 8, 5, 3, 2, 7, 0]\n",
      "\n",
      "Best attribute names\n",
      "['\"alcohol\"', '\"volatile acidity\"', '\"sulphates\"', '\"chlorides\"', '\"total sulfur dioxide\"', '\"pH\"', '\"free sulfur dioxide\"', '\"residual sugar\"', '\"citric acid\"', '\"density\"', '\"fixed acidity\"']\n"
     ]
    },
    {
     "data": {
      "image/png": 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v5uGHH6Zv375cdNFFvPnmm0mXZ9aiOSys4HTo0IGJEyfy+uuv82//9m/cfffd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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f322c0a4ac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3259f2ec88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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ec+ksB8s+DQznPOyjpqc8FWYpneFwebafVYVhf/Fkob6o/59nnXqukidZpyLy\nsohUwA8D/9upz0Zr1P2dwH3gZ0TkV0XkvxKRyflCIvJ5EXlTRN68f//+Mxmf+WSxmqC6aJuPaZLQ\nCISodCFQF+kmU1VC5FgYVgRVogpGBElzloTTSkQKgbQ+0PoUXvEaKa0ZykmKh4sQVHEuudcGwSuE\nGFFjkugqWBECmsTUR6w1GAWNio8BayV5nGKGP1CNKX4sEFURGY5fBiGX5CMbkoePnnjVq/9y6r9q\n8sxXoi7nynJu28qDP9XsqYLp3ZMixqfbXjUiF3y+aktOfWiMIcZ4PBIJBjGCV8UYQaMSVIbzmx5T\neo3EGCms0GkaOE/jo+KMEFXpoqIohUmDvTUn59IP/SC9jihK1DhcvUcxkvaJGjnXZOqb5mQ/K4KP\nZweFi7ad56L+f5516rlKnmTdnwG+BHwN+F9V9e8DiMjvBb6+Rt0O+AHgL6vq95MWbP175wup6hdU\n9a6q3r19+/Yzmp/5JLGKh160zRkZBDwJe2mTFw4gIliTxPz003AaIJSoeiw2p29MSGGNylkq5xAE\nJ2bI4kgR6JXYWBG8j2DSJKKT5K1KjMOgkAYYOwwS1hlCiEQBMYIzlhCU0hhU4/AHIilcoJoGluMl\nK8PE6kpdVjF35JzIcnYAkCFev/Lmzw8KnNu2EuBTzZ4qmN6d9VXPcmbwkbPbLmrrTIgoRow5GZ2U\niEbFSZosFSNY0eNBFwOFGIwx9EEpxSBy9no6I/ioGBFKkyaB+5jCJKvBPg7lTl4bBMGIGa7eo0RN\n+5hhoD7f5mlHIqg+ItwXbTvPRf3/POvUc5U8tmVV/XvAZ4DPqeqPn/ro14AfXaPud4B3VPWXh/c/\nRxoAMt+mbI4cbX+2w09rS+cjk8rR+0gflM3a8akbNfMmRQydwLiyNF1kVJxkCo8qw/aoIPgUfy2s\nYVye9VcPFj2v79S8tlNTWGFj5Fi26enBWoO1KbZ+e1oxbz2VEzTApCyYVgYzCEldGPoQ2Z44fFR2\nRgV9iGhQSqO8vFnS9oE7WzUjl4RKgLoQBh3HChhrMCSPu3CpTOGS9xP1JEtGSZ63cvYmrCy4YcPq\n89URrzz+1UBgJZ270+UZ6lu9vijv2pDE2wHl6W3DfpY0AK4QwDmoTHoqMgKFgKpQWmFkLaJpeBWR\n1A98xBlle1wcD+QC3N4s2awsh0vPrc2CwpkzWSuj0rHoPIWDlzZrrIVlG7g1qY4nO/3QnyDNu2yP\n0hyPsykccxGdD2yNCgorVOdi7Bt1cWZuqPORzdHZftb2ke3xk7PYL+r/51mnnqvkiUPNEHe/f27b\nkaoePq1iVX0feFtEvmfY9MMxVMbWAAAgAElEQVTAb3xoSzOfeKaVw0h6/F4xKdO2wq1yqiN14Xh1\ne4w1hqNlR104xs4l8bNJaRaN5+a44vbGiHmXYrRlYc7EWhdtjwi8ujPh9rRiWju2Ro6IIgJ1YXCk\nSb7NcYGYNGFrrWAtTOqUGw5K0BQPnpYlGpWtUUXn0xPJ1rhmXFoU4ZXNEdsbFaoRI0ph5dj7dsNr\nI1BaqJxQOMvIGYoiefiaHjKSKJskrisht6QQVeFOPPrISfliKBOG7cWQqlmd0g9ZlRtSM8+EYE6V\nMXK2HUPy3ldZRCIngwtA7YSqTIO2CEyqtIM1hlHpMG4YLEQZlwUhRApbsDmq8EFBBSfCzqSmdBaR\nNIk5Lix1YY7FvHCCRiiMYXtSpCcqlGldgAiNT5PwVWHxQ47+jWmVhNwZxmXxSBZMH1LYzVphWjvG\nlTvTR8eVRYZ+60NKnzztePTDtnH5ZKG+qP+ft2Odeq6Sq2753wT+poiUpNDQjz+lfOYFxlnDne2a\ne/sNnU8TWNYIN6YF7+4uqQpD6Qyt91hj+O13NvjVb+5TlspmVbBRW3aXPW2XUjf/8e+8ydIHfvlr\nuzS+x0lBjJHOKwfL/jgP/7temlI5y6dujAmqLPrA2w/niEJZCodN5Kj1vLpV8/Coo3LCrPFMSst3\n3Jzw9sM5+/Oe77w9onYpRPNg1uBMZHuz5pWdEUsf2Rk7Cmf5bt1g0aTBpvNgSRksISpRhOm4pBry\n8GsjqCjGwH4facLgWduU524lef4TC6MqpV6iMC1gMaRM+CF3f1SkrJyUV5REuXAgPuXe+5DqcSa9\nbgenteRs1g/D/nGYTxgZ6GJ6P7LJpnl3MkFcOCgLwXufBgqTPPEtZ4lRWbTJ0EkpOOc4mLds1I7b\nWxUhpEVMhS15aaNmXApIwUtbNU0f2J5YRs5x/6hhv+kxwGdujbHGMms8O9OSzbFjb+5BI8s+cGNU\nMWtT1tXNSVoIdj4Pv/UBZw0hRqLC9qgEFT51I00/numjItyclmfy8K2RR/Lnn7Zo6sL+P8wfPUs9\nV0leeJW5dHyILDrP/uJkpeG0siDK/sIza3oWXWRcphui6Xve2ksrbVHYGVsKm1ba7kzSStu9Rcc/\neG/G7rDS9rMvTfhtr2zy0sbokZW2h8uetx7OeevhjA8OW2JUnBXq0tIHWDYt9xce0ZQB8umdEc7B\ntw577h91BA1sVQWv7oy5MS4pnWHpAyEqfYDN2tD1kQ+Olvz6O2ml7byNGKNs1JZb0xG3p2mR1rz1\nvHPQsuh65n1Ps/TM2p5g0krbm1XJjQ2HWMtskVIGlyEmL1fSE4ZHk3irslFZNmpLFyL785OVtp++\nXfPSKK20fXu/4bDt6X2gQKkqx6R0FMbSDWmUjVecGKpCmFaW0hoWXeBg2aeFUU7YrguiSdsXXaBy\ncGtSc2ujTPnwndCFnrYLqEmhmUlpuTm2iEl554VN2zfHBXXheGWz5Na05ua0wmvgwWHP7rDSdlQK\nlXPUpaUwhtIJrU9efNN5Gh84ajw+pEnWG5OC7XHFzWl57DUvOs/DWcfRqT42rQtuDWVOr7R9pI/W\nBlSYteF42/bYndnvw/b/D1PPujzLwqu1BF9EfhT4LlX9T0TkU8BLqvrFj2jnI2TBz2QymWfjUlba\nnqrsvwB+P/DHh01z4K98ePMymUwm83GwTgz/h1T1B0TkVwFUdXeIyWcymUzmBWKdgFIvaTVJStUV\nucnZxYGZTCaTeQFYR/D/IvC3gdsi8h8Bvwj89JValclkMplLZ50fMf9rIvJF4A+QsrT+6GrVbSaT\nyWReHNb5EfP/VlV/DPgHF2zLZDKZzAvCOiGd7zv9Zojn/+DVmJPJZDKZq+JJP4Dyp0VkD/g+Edkd\n/vaAB8D/8twszGQymcyl8CQP/6eB28B/Nvy/DdxS1Ruq+pPPw7hMJpPJXB5P+rZMVVVPytCpVDUA\n/6KI/PSw2jaTyWQyLxDrxPC/ACxF5PtIP2/4LeBvXKlVmUwmk7l01hF8r+kLd/4w8BdU9c8DG1dr\nViaTyWQum3W+WmEuIj9J+i6df3rI0imu1qxMJpPJXDbrePh/jLTg6k+q6j3gdeA/vVKrMplMJnPp\nrLPS9j1OfZWCqn4T+JmrNCqTyWQyl886X4/8gyLySyJyICKNiLQi8tSfOMxkMpnMJ4t1Yvh/iRS/\n/++B3wX8GJDTMjOZTOYFY50YvlHVrwBOVXtV/aukL1LLZDKZzAvEulk6JfDrIvJTwD1gerVmZTKZ\nTOayWcfD/7Gh3E8AAfhu4F+4QpsymUwmcwU81sNffQWyqn5t2NQA/+HzMSuTyWQyl82TPPzve8Jn\nmUwmk3nBeFIMfywi309adPUIqvqlqzEpk8lkMlfBkwT/NeDPc7HgK/DPXIlFmUwmk7kSniT4v6Wq\nWdQzmUzm24R1snQymUwm823AkwT/Tz83KzKZTCZz5TzpF69+4XkakslkMpmrZZ2VttcWHyKz1nO4\n9PgYccawOXJMK4ez5qmfX3b7AhgjhKgAT2xvXdsuKjcpDSqwaONTj2u1//v7S76xO+Od3SVNH6mc\n5c5OxcsbI0onhKB0AQqX7E77Kk0f6WNg0XoOG8/Do5ajpqMPkcKlNm9NK6aVpfWRbz6c8f5hS9MG\nuhjo+56DZWAZIfhAYQIhRmYtLHtPVMAItRFKZxmXlnHliApNF2h9IERhXBqm45KRNRSlYMVQOMGq\n0PTK0bLl/qxh3vYEBVQYF5adjZJR4TDAsgssQsQKbI5KXpqUjCrLYeM5aDzeR5w1jEuhKhx1YalE\nWAbPWw+X3D9sOGp6EJg4S1k5HNBHwRkoC8O4tJTWoibSelAfaUOkbXuCClVZsDMu+OzLU25tjGh8\n4GjeMW890UAlBdtTy6vbY7ZHBfM2nfNZH9kcWV7fHvP6zTHTssAYubDP7y873t1ruHewYNkFSmsY\nlUIXYH/uWfQdqsK0coxLw6gs2JmU7IxLbkxKameYdZ73D1r2Fx0CbI0L7mzWbI3L4z7mQ+Rg0XHv\nsOFg0aPA9rjkla2K7VF5JffYh72Hr1oLLgtJP2Z1RZWLfAM4Iq3Q9ap690nl7969q2+++eaV2fMs\ntD5wb78hqlIVBmcMPkbaPmJEuDkteTjrHvv5ne2aytlLaz9E5d5+Q9N7qsLy2vYYY7iwvafZvip7\nUbl51/Pu7hKA12+MGZfusce12n933vLFb+zSx0jvwRjoQ6RpPCrC6zdG7ExKboxLduc9TfCICkaE\niPLwsOX+ouFo4Vn2EVTpYqQ0BkQoC6Hzgb15hyBUheFw4fnGgyP6YfCrnWHZBpY9dKTUMgdEwJMe\nZR1QWfCRYSCAUQGlg0Wbtm1UUJYVlYUuaCrrO2Y9hAAoRAEZbhsx4CQ1aA1M6/TbQBoVHwIeGJeO\nSeUIUVm2gTgcw62Nivf35hwuPTGAChiBtod+sL22UCgYl+wrLMSYyqX8OWHZKcaAM7AzKRBg0UNp\n4Y1bU1SVPiqtVzYqw0ubNfePWhBhVBhemo54eauiC5EHhx03Nws+fWODz33HNqPSnunz9/Yb3tmb\nc7DsqZxDJfLOgwVffThn5Azj2qX+5iNHTc9mXfDp22NGrmBnWrBVlzyct0Qi49IxLgoUZdkFfIi8\ntFXzxs0JAN94OOeDgwZnDaPSIgiLvsd75eXNEZ++Nb7Ue+zD3sOXVc+HRUS++DRtPS77OMEXkf+R\nlH55Iar6h9Yw5BvAXVV9sI4xnxTB9yHyzt4SZ4XigtF52Xne2Vvy+o0Ro+LRh6Q+RHxQXt8ZfajR\n/Xz7PkTuHTQ4Izhr6EMkROXOdo0z5kx7wBNtX5V9ZbPi/cP2TLnT7SicaeP8ca3aaXvPL/7WA5wV\nOq9Yk7J4H8waYhT6EIgo3/+pHQ6XnhvTkv1Fh0bwMbK36EDhvYMlyy5iDTRemRSWRd/jjGF/2bE3\n79goCqwTQoy8tbtAo6IiLNueMIh4F5LAA6xusVVesZI8DzN85gSsSwJeihBVCRHGDqIY6kJousBR\nA4VJO/qQBrTVjdGH9L+ySXALZ5hUjkXb03rFCNSlxVnBYDBGECCqHnu3MUCvYCWJvvcnA5Ud7C1d\namPuh20GSiscNkphYVwYxCT7RZXpuKLznt7DZ26PqZxL4u0js2XHxqjkaNmzMy25szlhc2KxCKrQ\nx8DLmyNuTmq+/9Nb1IVj2XveerAAlHkbqJxBRHhvf8E3dxdYYH/pCVHZnhSU1iBG8D4yrhyffWlC\nH6D3EWuE0hle3R498rS57AM3JiWqyt6iZ1TYR+6hPkTaPnBro+KNm5NLucfOs+49fFn1fBSeRfCf\nFNL5c5dkzwvHrPVEVQp78ajchUiIkRD0wh97LKyh855F59kclR+5/XmX3rvhfRoEPE0XmNbmTHtR\neaLtq7L3Z+0j5c63c7qN88e1aufeYYOPkbooaNVjjWHReaxJYm8NaIBvHcwpi4JF22NEWAx19x6W\nfRoAINKHJIg+RhCh7QOLZY+PQqcRF4Xdw4YQwVlD5yMqyaMcHHCEE3EXToR/0GaUJKgqHA8UFCAi\nBFWWPbgi0nbQdKlsFJKNw+gRY/ovQ719AGeTADS9px/qNSaJnI9CZQFjKSQ9sbQd2FOjUhi8fD11\nHKtj8Ol0gEIY/i96RUjbvUZKsfgQMCQ7iIaonoOjjts76VbXqDR9wLkea4UYlT70LFqltpbpuMAv\nofeBZd+zN2+5s+3ovTJre6IqpU1hilnbc7jsEQExhqARJIXKpIDpuEAU2i6w6DyIYX/RcmNaYYzQ\neM/UntwfzhpsiDw4akCgsI+K/Un/jyzay7vHLmpjnXv4sup5Xjxp0vb/etLfmvUr8Asi8kUR+fzl\nmHz1HC49VfH40XjWBKZ1wcGyf2yZqjDsL/xjP3+W9mdNoHRn7SmdPdP+qr2n2b4q++5e80i58+2c\nb+Oidr75YMnWqKTpI27Yt+lTDNOHJISTquDr95eMS8fDo57CGXxQjloPKLsLn8SMJPClExZDbHje\nBpY+Yk2k9QEflP3WY0SJUQlRUY3HHvFFj6R6bvux4ANBk5AH1VRGwQ8F2piENgnoicjHYeegJ/UF\nksAr0PTJthV9UIKPBFWIqZ1FF9Gh3jCEaMLKHpLIr55MhmZp+9SYDhu6kMJIUSEiRE11qVmFo5RC\n4GHjsVboQqTxEWsMewvPqLB0QVl0kXnj6YaK60I4aDyqcG+/BeCo6RHgcBEobLJs2UWOmkhdpCeH\n1flb+JO6rBVUhAeHPd5HFr3S+kjpDLNmdWQnlM6wN+/ZnflH+vzZcpY2xEu7xy5inXv4sup5Xqzz\ni1ffLSI/JyK/ISJfW/2tWf8/qao/APwI8KdE5PddUP/nReRNEXnz/v37z2j+1bCadHnS56U1+HiR\nvCSsSPJSL6H9i+wxwpn2V+09zfZV2db7R8qd3/d8Gxe10/ieurCEGLFJtYmqGCOswoVuCNM4k7x0\nK+mzwYknBkWGoHQAjAheFSNCH+Pg5RqOo48K1thTIn6yGNyceXdWOB/hlNceFFSTPSECIscCbt1J\n+eNwzmMrhUH6hkHsZIABSf8FQozpczlb7+r0i5w0YUi2KWnOYPU6rsprCuMcnyBN4bhV74uqwzkn\nXROT/lsrRI141WHwSi0aw3FiQBtSLT4qIoLXeBy28zESCThriKqrKQWCP6krPZUonUaipsF5dUwX\n3R92dc01PLEfG4EY9dLusYtY5x6+rHqeF+sElX4G+MskB+r3A38N+OvrVD78Hi6q+gHwd0m/mHW+\nzBdU9a6q3r19+/a6dl8pq0mXJ33ehYgzj7/rg+pTO8K67V9kT1TOtL9q72m2r8pWzj1S7vy+59u4\nqJ3aFTR9wBqTPFiSYMdBICB5ybUTfFRKSeVEJImcgrGCxuSHW5JAuSGmXhiDBZR4LKBJMMMpzT2R\n/njm3aPe/Rk0CShD/Fwk2WMHhTWD6AZ/Uj7GQcqekOtgBstW+iusbjRN/xWsGQYwPVvv6vSvRH11\nTKsBQOPJa7MqL6AiJyOMgDVyfHObIVSVigjEIXwVFCMGJ4I9dVAxcizq1RBSccMA7sScyRIzWHxI\nk5MrDz8NkHpyDkQoxWBEEDHHx3TR/RFW11zsE/txCpfJpd1jF7HOPXxZ9Twv1rFipKr/O2mC9y1V\n/TOs8T06IjIRkY3Va+CfBf7+RzH2ebE5crT94y/itLbMmp6t0QUB/IG2j2yPP1zW6/n2p7Wl82ft\n6Xw40/6qvafZvir72k79SLnz7Zxv46J2vuPWiINlR12kODqQXseIsymrZN72fOb2iEXnublR0PuI\ns8JG5QDhxtgN4qhUhaXzyri0dCEyqSwjZwjRULk0+bldOaIKxgjWJBFZZeFcNASf9/JXYikMQm+S\nF7byUN1QoBoyXyIpPr+6Z82wsz3R1zSROghxXSTbVhRWsM6kJ6Bh0nZcpmHB2ZOwjF3Zw9mBanWT\nVkVqbNBMSnsSDjKkAcoakJgmdJ0ReoWbtSMEpbSG2hlCjOyMHcs+UNqUkjqpHaWsQnLKVu0QgTvb\nFQAbdYECm2NLP8SyRqVhozY0/TCJO5yMsTupKwRFVLm1WeCcYVwIlUtzL6u5odN0PrIzKbgxdY/0\n+bPlApU1l3aPXcQ69/Bl1fO8WEfwG0nD8v8nIj8hIn8EeGmN/V4GflFEfh34FeB/VtWf/wi2Pjem\nlUvhhHDxhSytwRqDtRfJS5qZNyKMyw93kc+3PynTez+870NERKhL+0h7T7N9Vfb2tHqk3Ol2zrfx\nuHbubNbHXo5IWiNQOUuIihWbYsoCL29NsGIYV0VKX7OWSeUoHGzW5SBihsImT9EN7n9VWMajAmfS\n00FhDLc26ySSIYUXRCPOpcFlJZZwkuHCqfdwSvAHb34VslFVrKRUTSuGqrTUZSprjj3/VNaYU2EY\nUttomnisC0dhhtRJTZk7dZH6jGF4grGGqkz7WVI5a9PfaoDSwWYhDTzlaqAh1T0u0rlSBScG1TSQ\nWpPswESMGLY2yuMBT4xQF5ZRUSQP3wiFLRhXjsIZmjagBAqXyuxMkuAXTphWBZt1QYgRHyKjwrE5\nKtLTSIhYMaCpzxSDqPchUpWWcekojGF7XCGkJ8Danb0//JB9dmuj5uakIkQ97vPn+3CIyrhyl3aP\nXdTGOvfwZdXzvHhqHr6I/CDwZWAb+LPAFvDTqvpLl23MJyUtEx7NrbXDY/Hj8vDPf37Zefg+RN4/\naI/z8F/dGmGtrJWH/zjbLiq36P2ZPPxRYR97XOfz8LsQ8CHllgQVlk0PYnj9xojtccHNScXDWUcb\nA6LJ01WBh4cN9xcth/Oepo+oKl0MlMaCGMoi3Ti7sxYjhsoJe4uOtx8u6KMOoQboPTQeWgaRZsiw\nGc5pSfKKfTjxoKsC6gLmTXq/WYNzBbUzaV1BUDR4DtshzDJM6q6urJHkpevwemPkjmPl/397dx8k\nyV3fd/z96e552p3b29u7i3TmhM6AeQhUJNAFsBVcICiZJ4tKoAqRUEQ2FAU4MXYVtnGcIk5CYjsu\npwgxJjy4XCTYQY4cOQrhycaikLHAnB4RRjgKCJB04h739mZn56G7v/mje3b3RruzM6uZ2dmd76tq\nant6un/9/XXvfKen5/f7dZIkJIJKsUC1GNBOsrO9xLJvQQerRR6/sMLFvB1+QlZuM8n6EkDWCKwc\ngKLsUkshzH5v6JxrGNmPuZ12+PvKAYUwZLlllCJx5cFZzIzYoBmnVIshl+0vcWqpiYKASiHg0GyZ\ny/eXaMbGudpaO/yrrtjPTCnatB1+MQxX2+F/51w9a4dfylrWxLGxtNJirlLg2OFZylHEQrX4hHb4\nlSjCyDrg9WqHXy4ECLESxyNrh7/d9/CwytmuobTD3wmTlPAhO+Oot2IW62u95+ZnsrOKTq/DXq8P\ne/sCipFoxmvXUDfbXr+xbbRctRSCjFoj3bJenfUfO7/CI+eXefhsnVacUghDnrpQ5mC1TLEgkgSa\nsVGMsqZqWPZDYL2VYpZQa8TUmjFnLja50GgRJylRGDFXLnCoWmSmGNJOU75/ZpnHLjSyjjppQrsd\nc74R04yzpoQzYUozSVhuQr2dkFjWN6AYiFIUUimGVEoRgaDeTFhpZz1tZ0sB85UixTAgKopAAbOR\nsLxj08VGkzMXG1xsxiQYgYlKIeRAtZjtF8HFRpL9yKmsR+hl1RLlQsjFVptz9YQkTilGYrYooqhI\nuRBQCkQ7ifnO2TqnLmQ9bSWYKYSUihFRAM04a9IZRdmxCYOQIDAasZHGRiNJidttWgmUiwXmZ4o8\n90f2caBaot7KetrWmgkKjZACC/tCjuyfYWG2QK0Rc7bWZKmZMl/JOvQdOzxDKVrradv9P7/UaPHo\nuQYnL6yw3IopRSHVomincPpim5V2C0zMliNmCiGVYsTCbJH9M0UOVbN9XG/HPL7Y5FzeF+HAbIHL\n5yrMVQqX9LRdWmnz+NIK55eznrYLM0Uuny8xVx5eT9thvIdHnQt6GWrCl3Q7G/xENYqhkyct4Tvn\n3KQbVserjvesmy4Dr2etM6NzzrldYsuEb2Z3dc36iqR+O14555ybEFsmfEkL654GwDXA5SOLyDnn\n3Ej0c0nnLtZ6e8fAd4G3jjIo55xzw9dPwn+OmTXWz5BUGlE8zjnnRqSf9kJ/tcG8O4cdiHPOudHa\n9Axf0uXAU4CKpOez1jt9DpgZQ2zOOeeGqNclnZ8CbgKOAr/DWsJfAv7FaMNyzjk3bJsmfDP7BPAJ\nSa83sz8ZY0zOOedGoJ9r+NdImu88kXRA0vtHGJNzzrkR6Cfhv8rMFjtPzOw88OrRheScc24U+kn4\n4fpmmJIqgDfLdM65XaafdvifBL4o6Q/IOmD9LNldr5xzzu0i/Yyl8x8k3Q+8gqylzr81s8+PPDLn\nnHND1ddtWPI7VX0OQNK1kj5kZj830sicc84NVV8JX9LVwJuAN5KNpfM/RxmUc8654evV0/aZwI1k\nif4scDPZDVNeNqbYnHPODVGvM/wHgTuAnzazhwAk/eJYonLOOTd0vZplvh54HLhd0sckvZy14RWc\nc87tMpsmfDO71czeCDwb+BLwi8Blkj4s6foxxeecc25Itux4ZWbLZvaHZvZasoHU7gXeO/LInHPO\nDVU/PW1Xmdk5M/uImV03qoCcc86NxkAJ3znn3O7lCd8556aEJ3znnJsSnvCdc25KeMJ3zrkp0ddY\nOs51xElKrRmztBLTjBOacQoYxSigHEXMVSKqpYgo3PpcYrtlddY7v9ziwkqbWjPGMAICZksh+ysF\nDswWKUcBjThlaSUmTlOiIBgovl7xdsqbLQaYoN5Mn7CNRivmu+fqfOfUMrVmG0nsr0QUQ1FvGVEI\n85USRxcqXLavRLnY/9txo1g62wU2fW2Qevfaxnb2n9t5MrPRbkAKgRPAo3lb/k0dP37cTpw4MdJ4\n3PY144STiw1SMyQ4W2vRThMwUQgDFqoFMBFIHJkvU4rCoZfVWa8Rx1yox8RJyrl6izQxwlAcmC0S\nBQGVYsDSSsyhfUX2lQtEQUCcpjTbaV/x9Yq3VAiIgoDlVptHz60AcHRhhplitLqNC/U23/rhBUJg\nplRgpRVzvt7i/52qESrgmivn2Vcp0U4SyoWAciHiqivm2VcubCuWznbbaYpMRKGe8Nog9e61je3s\nPzc6ku4ys+P9LDuOj+l3A98aw3bcCMVJysnFxmoiOVtrEQZiX6mTUMW5WptSFBCF4uRigzhJh1pW\nZz0wao2EMITlVsJMMWJ+tkilELLcjBHwvTN1wgBqjSS7bQ9kZ+SlaMv4esU7W4qy5JeknKu12Vcu\nUC0XOFtrrZ4Fm4wTD5+l0UpZmC2z0opJU1hcbnPZXJmF2SIPPl7DLKVSCEkNokDc94NFGq144Fg6\ndStFAedqLc4tN1eT9Hbq3Wsb29l/bnKMNOFLOgq8Bvj4KLfjRq/WjEnNKIQB9WaC5dMdURiQmrHS\njink0/VNktd2y+qs10pSUjPasWFmRIFW1zMTF5stkjT75tApZ72t4usVb8dyK5sXhQGFMMDMaLQS\nAB45W8cMZoohFxpNzESt1cZMFAsh5VJIQsqZWmM1ZgmSNOXscnPgWNbHFAYiDLQay3bq3Wsbg5Tj\nJs+oz/A/APwy4KcCu9zSSkypkP27XGy0KW7wdb4YBSytZImmVAhYrG+cELZbVme9WiOhGAUsN2MK\n0aX/woVQ/HCpxWw5otZILylnvV7x9Yq3oxPDWrwhF1baAHz/zDJzMwUKUcCZi22iUJxfjikW1sYe\nrBYjHjnXWI15qRFTLRf4QT5vkFi6Y1ofS7d+6t1rG4OU4ybPyBK+pNcCp8zsri2We7ukE5JOnD59\nelThuCepc7kimzbC4IkDp4YScZo+YXpYZXXWW/trhLp03UDQTlIKQbbOZnH0iq9XvJvNC5TVBWAl\nTikXQgKgnaaEeSzrP5yiUDTTZHXdJDUKgWjGW1zS2SCW7tfWx9Ktn3r32sYg5bjJM8oz/GuBGyQ9\nDHwKuE7SJ7sXMrOPmtlxMzt++PDhEYbjnoxOos2mRbJBQknMVhPF+ulhlXVpsk+zdbsaHaSWXXJo\np9k6m8XRK75e8W42r3MdHqASBTTaCSlQCAKSPJZ2vLZ8nBilIFxdNwxEOzVKUe+WOhvF0v3a+li6\n9VPvXtsYpBw3eUZ2xMzsV83sqJkdI7tz1l+Y2ZtHtT03WnOViGY7SwL7ygVa8RMvk7TilLlK3pqm\nnTI/s3Hy2m5ZnfWq5ZBWnDJbii5JogDtxLhsrshyI6ZaDi4pZ71e8fWKt6MTw1q8CfsrWQubpx6a\nZaneph2nHNpXIE6MA7MRrfbah1OtFXN0obwa81w5otZoc0U+b5BYumNaH0u3furdaxuDlOMmj39E\nu75USxGBRDtJmSmFKJ/uiJOsuV6lENHOp2c2aVe+3bI66xXDgECiEAlJq5cv4iRFMvaVioSBMGO1\nnPW2iq9XvB2zxWxenJEpNh4AAA0sSURBVKS0kxRJlIvZB8vRgzNIUG8l7C+XkIxqsYBktNoJjWZC\nSMChank1ZjMIg4CDs6WBY1kfU5IaSWqrsWyn3r22MUg5bvKMJeGb2Ze2aoPvJlsUBhyZLxMnRrOd\ncrBaJE5SLjZbXGy0aScpC9UCzTglTowj8+VNO+dst6zOeiCq5ZAkgZlCQL0Vc365yUo7YaYYYsCV\nh2ZI0uysF4GZEacpy814y/h6xbvczDohhYFYqBa42GhTa7Q5WC2uXteWiePHDlIuBpxbblApRpgZ\n87MFfrjU4GytybMvr2IGK+1k9Zr7VVfMb9n5aqNYOnVrxikL1SILsyWa7fSS1wapd69tbGf/uckx\n8o5Xg/COV5MvTlLqrZjFetY7th2noKx5YjmKmJ+JmCn239N2O2V11jtbyz4glhoxoYzUAvaVQ/aV\nCxysFimGAa0kZbG+1lN0kPh6xdspr1oKQUatkT5hG41WzKOLdR58POtpG0gszEYUgoCLzZRiCHOV\nEscOVTg4O3hP2+5YOtsFNn1t0J62wyjHjdYgHa884Tvn3C42aT1tnXPOTQBP+M45NyU84Tvn3JTw\nhO+cc1PCE75zzk0JT/jOOTclPOE759yU8ITvnHNTwhO+c85NCU/4zjk3JTzhO+fclPCE75xzU8IT\nvnPOTQlP+M45NyU84Tvn3JTwhO+cc1PCE75zzk0JT/jOOTclPOE759yU8ITvnHNTwhO+c85NCU/4\nzjk3JTzhO+fclPCE75xzU8ITvnPOTQlP+M45NyU84Tvn3JSIdjqAJytOUmrNmKWVmDhNiYKAuUpE\ntRQRhXvz82zcdZ7GfTxsvg/dJBhZwpdUBr4MlPLt3GJm/2qY22jGCScXG6RmlAoBpUJEnKacW26x\nWG9zZL5MKQqHuckdN+46T+M+Hjbfh25SjPLUoglcZ2ZXAVcDr5T04mEVHicpJxcbRKGYLUVEQVaV\nKAiy56E4udggTtJhbXLHjbvO07iPh833oZskI0v4lqnlTwv5w4ZVfq0Zk5pR2OTrcCEMSM2ot+Jh\nbXLHjbvO07iPh833oZskI714KCmUdC9wCvgzM/vasMpeWokpFXqHXyoELNb3zhtp3HWexn08bL4P\n3SQZacI3s8TMrgaOAi+U9LzuZSS9XdIJSSdOnz7dd9mdH756CSXidO98VR53nadxHw+b70M3ScbS\nPMDMFoEvAa/c4LWPmtlxMzt++PDhvsuMgmDLN0lituWbbTcZd52ncR8Pm+9DN0lG9l8m6bCk+Xy6\nArwCeHBY5c9VIprt3m+kZjtlfmbXtzxdNe46T+M+Hjbfh26SjPK04ghwu6T7ga+TXcP/9LAKr5Yi\nAon2Jq0b2klKIDFT3DtvpHHXeRr38bD5PnSTZGT/ZWZ2P/D8UZUfhQFH5sucXGzQirMfxkKJxIxm\nO3sTHZkv76lOLeOu8zTu42Hzfegmya4+rShFIUcPVKi3YhbrMc00IQoCDlWLzBT3Zg/Gcdd5Gvfx\nsPk+dJNiVyd8yM6g5ipF5irFnQ5lbMZd52ncx8Pm+9BNAj+1cM65KeEJ3znnpoQnfOecmxKe8J1z\nbkrIbGjjmT1pkk4D3xvT5g4BZ8a0rVHbS3WBvVUfr8vk2iv1udLM+hqmYKIS/jhJOmFmx3c6jmHY\nS3WBvVUfr8vk2mv16Ydf0nHOuSnhCd8556bENCf8j+50AEO0l+oCe6s+XpfJtdfqs6WpvYbvnHPT\nZprP8J1zbqpMRcLPb7V4j6QnDM8sqSTpZkkPSfqapGPjj7B/W9TlJkmnJd2bP962EzH2S9LDkr6R\nx3pig9cl6YP5sblf0gt2Is5+9FGXl0q6sO7YvG8n4uyHpHlJt0h6UNK3JP141+u76bhsVZddc1yG\nYdcPntandwPfAuY2eO2twHkze4akG4HfAt44zuAG1KsuADeb2T8bYzxP1svMbLO20K8Cfix/vAj4\ncP53UvWqC8AdZvbasUWzff8J+JyZvUFSEZjpen03HZet6gK757g8aXv+DF/SUeA1wMc3WeR1wCfy\n6VuAl0vSOGIbVB912WteB/xXy3wVmJd0ZKeD2sskzQE/Cfw+gJm18luUrrcrjkufdZkqez7hAx8A\nfhnY7D5zTwF+AGBmMXABODie0Aa2VV0AXp9/zb5F0hVjimu7DPiCpLskvX2D11ePTe6RfN4k2qou\nAD8u6T5Jn5X03HEGN4CnAaeBP8gvHX5c0mzXMrvluPRTF9gdx2Uo9nTCl/Ra4JSZ3dVrsQ3mTVzT\npT7r8r+BY2b294A/Z+2by6S61sxeQHaJ4Ock/WTX67vi2OS2qsvdZF3grwL+M/Cn4w6wTxHwAuDD\nZvZ8YBl4b9cyu+W49FOX3XJchmJPJ3zgWuAGSQ8DnwKuk/TJrmUeAa4AkBQB+4Fz4wyyT1vWxczO\nmlkzf/ox4JrxhjgYM3ss/3sKuBV4Ydciq8cmdxR4bDzRDWarupjZkpnV8unPAAVJh8Ye6NYeAR4x\ns6/lz28hS5rdy+yG47JlXXbRcRmKPZ3wzexXzeyomR0DbgT+wsze3LXYbcA/zaffkC8zcWcr/dSl\n6zrqDWQ/7k4kSbOS9nWmgeuBB7oWuw14S94q5MXABTM7OeZQt9RPXSRd3vltSNILyd57Z8cd61bM\n7HHgB5Kelc96OfA3XYvtiuPST112y3EZlmlppXMJSf8GOGFmt5H9oPPfJD1EdmZ/444GN6Cuuvy8\npBuAmKwuN+1kbFu4DLg1f69FwB+Z2eckvQPAzP4L8Bng1cBDQB34mR2KdSv91OUNwDslxcAKcOMk\nnljk/jnwh3mrlu8AP7NLjwtsXZfddFyeNO9p65xzU2JPX9Jxzjm3xhO+c85NCU/4zjk3JTzhO+fc\nlPCE75xzU8ITvhsqSUk+6uADkv6HpI0Gq+q3rJcqHxVU0g2SuntJrl92XtK7trGNX5f0nq55v7Zu\n9MRk3fTPD1j20/IB+QaN6X2SvpkPkXGPpL8/aBnObcQTvhu2FTO72syeB7SAd6x/Me+sM/D/nZnd\nZma/2WOReWDghL/Jtv5dXoerWavP1Wb2wQGLehoD9uuQ9BKyjlvPz4fIuJ6sx+i25T3InfOE70bq\nDuAZko7lY5H/HtnYJVdIul7SnZLuzr8JVAEkvVLZ2OV/CfyjTkHKxvr/3Xz6Mkm35gNe3SfpJ4Df\nBJ6en4n/dr7cL0n6en6m/K/XlfVrkr4t6c+BZzEASa9Tdt+EeyR9QdLfyedfl8dyb16n2Tyml3W+\nHUiKJP1HSX+dx7TR/QqOAKfNrAVgZqc7vVglvSjfZ/flMcxIqkj6hLKx+O9WPoaPpLdJ+lT+Demz\n+bz3rtv2nh733W3CzPzhj6E9gFr+NwL+F/BO4BjZCJ8vzl87BHwZmM2f/wrwPqBMNgrjj5EN0PXH\nwKfzZW4Cfjefvhn4hXw6JBv/6BjwwLo4rie7Z6nITmw+TTZU7jXAN8jGRZ8j6y36nq3qs+75AdY6\nLL4D+K18+rPAi/Lpah7XK4A/Xbfuu4D35tMl4B7gqV3lzwH3A98GPgS8JJ9fBr4LvCB/vj/fxq8A\nH8vnPRf4HlAE3pZPH8hfezXwe+v2x+eAn9jp/xd/jPfhX/XcsFUk3ZtP30E2dMWPAN+zbOx0gBcD\nfxf4Sj4cQRG4E3g28F0z+78AygaH22io4euAtwCYWQJckHSga5nr88c9+fMq2QfJPuBWM6vn27ht\nwPo9FfhjSZeTJe2/zed/BfiApD8C/sTManribRWuB56z7rr+/jym73cWMLMlZXeQegnwMuCW/DeG\nB4Dvm9nd+XIX8vj/AfDb+bxvSnoMeEZe3BfM7Py6bb+qa388E/irAevvdjFP+G7YViy79r0qT3zL\n62cBf2Zmb+pa7mqGN8yugN8ws490beMXnuQ2PgT8ezP7jKRXkA+3a2bvzz88XgN8XdJLN4npXWb2\nxV4bsOy+DLcDt0v6G7I7sH1zk7h73ayne5+/38x+v9e23d7m1/DdTvgqcK2kZwDk16KfCTwI/Kik\np+fLvWmT9b9Idqmoc4/fOeAi2dl7x+eBn13328BT8uvtXwb+YX7tex/w0wPGvh94VNmnWGeUVSQ9\n3czuN7PfIDuLftYmMb2r8yOqpGdJqqwvXNJzOvsldxXZpZlvAlfmZ/9ImpMU5vX5J511yX4DeGiD\nuD8PvDX/bQFJR7WHhwF2G/MzfDd2ZnZa0k3Af5dUymf/SzP7W2V3i/o/ks4Afwk8b4Mi3g18VNJb\ngQR4p5ndKekrkh4APmtmv5QnwDvzbxg14M1mdrekm4F7yRLpHQOG/+tk490/Avw1WYIFeE/ewiYl\nuwb/hXx+KOk+sktbHyK7JHRvHtMpstsFrlcFPihpf163bwNvN7OmpDcBH5ZUJhvZ8Tqym3Z8RNI3\ngDbwFjNrdV9Oyr+RPBv4av7aReAfA73uwev2GB8t0znnpoRf0nHOuSnhCd8556aEJ3znnJsSnvCd\nc25KeMJ3zrkp4QnfOeemhCd855ybEp7wnXNuSvx/0LrvZGU5pEkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f322c6b8940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "__author__ = 'mike-bowles'\n",
    "import urllib.request, urllib.error, urllib.parse\n",
    "import numpy\n",
    "from sklearn import datasets, linear_model\n",
    "from math import sqrt\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "def xattrSelect(x, idxSet):\n",
    "    #takes X matrix as list of list and returns subset containing columns in idxSet\n",
    "    xOut = []\n",
    "    for row in x:\n",
    "        xOut.append([row[i] for i in idxSet])\n",
    "    return(xOut)\n",
    "\n",
    "#read data into iterable\n",
    "target_url = \"http://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-red.csv\"\n",
    "data = urllib.request.urlopen(target_url)\n",
    "xList = []\n",
    "labels = []\n",
    "names = []\n",
    "firstLine = True\n",
    "for line in data:\n",
    "    if firstLine:\n",
    "        names = line.strip().decode().split(\";\")\n",
    "        firstLine = False\n",
    "    else:\n",
    "        #split on semi-colon\n",
    "        row = line.strip().decode().split(\";\")\n",
    "        #put labels in separate array\n",
    "        labels.append(float(row[-1]))\n",
    "        #remove label from row\n",
    "        row.pop()\n",
    "        #convert row to floats\n",
    "        floatRow = [float(num) for num in row]\n",
    "        xList.append(floatRow)\n",
    "\n",
    "#divide attributes and labels into training and test sets\n",
    "indices = range(len(xList))\n",
    "xListTest = [xList[i] for i in indices if i%3 == 0 ]\n",
    "xListTrain = [xList[i] for i in indices if i%3 != 0 ]\n",
    "labelsTest = [labels[i] for i in indices if i%3 == 0]\n",
    "labelsTrain = [labels[i] for i in indices if i%3 != 0]\n",
    "\n",
    "#build list of attributes one-at-a-time - starting with empty\n",
    "attributeList = []\n",
    "index = range(len(xList[1]))\n",
    "indexSet = set(index)\n",
    "indexSeq = []\n",
    "oosError = []\n",
    "\n",
    "for i in index:\n",
    "    attSet = set(attributeList)\n",
    "    #attributes not in list already\n",
    "    attTrySet = indexSet - attSet\n",
    "    #form into list\n",
    "    attTry = [ii for ii in attTrySet]\n",
    "    errorList = []\n",
    "    attTemp = []\n",
    "    #try each attribute not in set to see which one gives least oos error\n",
    "    for iTry in attTry:\n",
    "        attTemp = [] + attributeList\n",
    "        attTemp.append(iTry)\n",
    "        #use attTemp to form training and testing sub matrices as list of lists\n",
    "        xTrainTemp = xattrSelect(xListTrain, attTemp)\n",
    "        xTestTemp = xattrSelect(xListTest, attTemp)\n",
    "        #form into numpy arrays\n",
    "        xTrain = numpy.array(xTrainTemp); yTrain = numpy.array(labelsTrain); xTest = numpy.array(xTestTemp); yTest = numpy.array(labelsTest)\n",
    "        #use sci-kit learn linear regression\n",
    "        wineQModel = linear_model.LinearRegression()\n",
    "        wineQModel.fit(xTrain,yTrain)\n",
    "        #use trained model to generate prediction and calculate rmsError\n",
    "        rmsError = numpy.linalg.norm((yTest-wineQModel.predict(xTest)), 2)/sqrt(len(yTest))\n",
    "        errorList.append(rmsError)\n",
    "        attTemp = []\n",
    "\n",
    "    iBest = numpy.argmin(errorList)\n",
    "    attributeList.append(attTry[iBest])\n",
    "    oosError.append(errorList[iBest])\n",
    "\n",
    "print(\"Out of sample error versus attribute set size\" )\n",
    "print(oosError)\n",
    "print(\"\\n\" + \"Best attribute indices\")\n",
    "print(attributeList)\n",
    "namesList = [names[i] for i in attributeList]\n",
    "print(\"\\n\" + \"Best attribute names\")\n",
    "print(namesList)\n",
    "\n",
    "#Plot error versus number of attributes\n",
    "x = range(len(oosError))\n",
    "plt.plot(x, oosError, 'k')\n",
    "plt.xlabel('Number of Attributes')\n",
    "plt.ylabel('Error (RMS)')\n",
    "plt.show()\n",
    "\n",
    "#Plot histogram of out of sample errors for best number of attributes\n",
    "#Identify index corresponding to min value, retrain with the corresponding attributes\n",
    "#Use resulting model to predict against out of sample data.  Plot errors (aka residuals)\n",
    "indexBest = oosError.index(min(oosError))\n",
    "attributesBest = attributeList[1:(indexBest+1)]\n",
    "\n",
    "#Define column-wise subsets of xListTrain and xListTest and convert to numpy\n",
    "xTrainTemp = xattrSelect(xListTrain, attributesBest)\n",
    "xTestTemp = xattrSelect(xListTest, attributesBest)\n",
    "xTrain = numpy.array(xTrainTemp); xTest = numpy.array(xTestTemp)\n",
    "\n",
    "#train and plot error histogram\n",
    "wineQModel = linear_model.LinearRegression()\n",
    "wineQModel.fit(xTrain,yTrain)\n",
    "errorVector = yTest-wineQModel.predict(xTest)\n",
    "plt.hist(errorVector)\n",
    "plt.xlabel(\"Bin Boundaries\")\n",
    "plt.ylabel(\"Counts\")\n",
    "plt.show()\n",
    "\n",
    "#scatter plot of actual versus predicted\n",
    "plt.scatter(wineQModel.predict(xTest), yTest, s=100, alpha=0.10)\n",
    "plt.xlabel('Predicted Taste Score')\n",
    "plt.ylabel('Actual Taste Score')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### readURL.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0200,0.0371,0.0428,0.0207,0.0954,0.0986,0.1539,0.1601,0.3109,0.2111,0.1609,0.1582,0.2238,0.0645,0.0660,0.2273,0.3100,0.2999,0.5078,0.4797,0.5783,0.5071,0.4328,0.5550,0.6711,0.6415,0.7104,0.8080,0.6791,0.3857,0.1307,0.2604,0.5121,0.7547,0.8537,0.8507,0.6692,0.6097,0.4943,0.2744,0.0510,0.2834,0.2825,0.4256,0.2641,0.1386,0.1051,0.1343,0.0383,0.0324,0.0232,0.0027,0.0065,0.0159,0.0072,0.0167,0.0180,0.0084,0.0090,0.0032,R\n",
      "\n",
      "0.0453,0.0523,0.0843,0.0689,0.1183,0.2583,0.2156,0.3481,0.3337,0.2872,0.4918,0.6552,0.6919,0.7797,0.7464,0.9444,1.0000,0.8874,0.8024,0.7818,0.5212,0.4052,0.3957,0.3914,0.3250,0.3200,0.3271,0.2767,0.4423,0.2028,0.3788,0.2947,0.1984,0.2341,0.1306,0.4182,0.3835,0.1057,0.1840,0.1970,0.1674,0.0583,0.1401,0.1628,0.0621,0.0203,0.0530,0.0742,0.0409,0.0061,0.0125,0.0084,0.0089,0.0048,0.0094,0.0191,0.0140,0.0049,0.0052,0.0044,R\n",
      "\n",
      "0.0262,0.0582,0.1099,0.1083,0.0974,0.2280,0.2431,0.3771,0.5598,0.6194,0.6333,0.7060,0.5544,0.5320,0.6479,0.6931,0.6759,0.7551,0.8929,0.8619,0.7974,0.6737,0.4293,0.3648,0.5331,0.2413,0.5070,0.8533,0.6036,0.8514,0.8512,0.5045,0.1862,0.2709,0.4232,0.3043,0.6116,0.6756,0.5375,0.4719,0.4647,0.2587,0.2129,0.2222,0.2111,0.0176,0.1348,0.0744,0.0130,0.0106,0.0033,0.0232,0.0166,0.0095,0.0180,0.0244,0.0316,0.0164,0.0095,0.0078,R\n",
      "\n",
      "0.0100,0.0171,0.0623,0.0205,0.0205,0.0368,0.1098,0.1276,0.0598,0.1264,0.0881,0.1992,0.0184,0.2261,0.1729,0.2131,0.0693,0.2281,0.4060,0.3973,0.2741,0.3690,0.5556,0.4846,0.3140,0.5334,0.5256,0.2520,0.2090,0.3559,0.6260,0.7340,0.6120,0.3497,0.3953,0.3012,0.5408,0.8814,0.9857,0.9167,0.6121,0.5006,0.3210,0.3202,0.4295,0.3654,0.2655,0.1576,0.0681,0.0294,0.0241,0.0121,0.0036,0.0150,0.0085,0.0073,0.0050,0.0044,0.0040,0.0117,R\n",
      "\n",
      "0.0762,0.0666,0.0481,0.0394,0.0590,0.0649,0.1209,0.2467,0.3564,0.4459,0.4152,0.3952,0.4256,0.4135,0.4528,0.5326,0.7306,0.6193,0.2032,0.4636,0.4148,0.4292,0.5730,0.5399,0.3161,0.2285,0.6995,1.0000,0.7262,0.4724,0.5103,0.5459,0.2881,0.0981,0.1951,0.4181,0.4604,0.3217,0.2828,0.2430,0.1979,0.2444,0.1847,0.0841,0.0692,0.0528,0.0357,0.0085,0.0230,0.0046,0.0156,0.0031,0.0054,0.0105,0.0110,0.0015,0.0072,0.0048,0.0107,0.0094,R\n",
      "\n",
      "0.0286,0.0453,0.0277,0.0174,0.0384,0.0990,0.1201,0.1833,0.2105,0.3039,0.2988,0.4250,0.6343,0.8198,1.0000,0.9988,0.9508,0.9025,0.7234,0.5122,0.2074,0.3985,0.5890,0.2872,0.2043,0.5782,0.5389,0.3750,0.3411,0.5067,0.5580,0.4778,0.3299,0.2198,0.1407,0.2856,0.3807,0.4158,0.4054,0.3296,0.2707,0.2650,0.0723,0.1238,0.1192,0.1089,0.0623,0.0494,0.0264,0.0081,0.0104,0.0045,0.0014,0.0038,0.0013,0.0089,0.0057,0.0027,0.0051,0.0062,R\n",
      "\n",
      "0.0317,0.0956,0.1321,0.1408,0.1674,0.1710,0.0731,0.1401,0.2083,0.3513,0.1786,0.0658,0.0513,0.3752,0.5419,0.5440,0.5150,0.4262,0.2024,0.4233,0.7723,0.9735,0.9390,0.5559,0.5268,0.6826,0.5713,0.5429,0.2177,0.2149,0.5811,0.6323,0.2965,0.1873,0.2969,0.5163,0.6153,0.4283,0.5479,0.6133,0.5017,0.2377,0.1957,0.1749,0.1304,0.0597,0.1124,0.1047,0.0507,0.0159,0.0195,0.0201,0.0248,0.0131,0.0070,0.0138,0.0092,0.0143,0.0036,0.0103,R\n",
      "\n",
      "0.0519,0.0548,0.0842,0.0319,0.1158,0.0922,0.1027,0.0613,0.1465,0.2838,0.2802,0.3086,0.2657,0.3801,0.5626,0.4376,0.2617,0.1199,0.6676,0.9402,0.7832,0.5352,0.6809,0.9174,0.7613,0.8220,0.8872,0.6091,0.2967,0.1103,0.1318,0.0624,0.0990,0.4006,0.3666,0.1050,0.1915,0.3930,0.4288,0.2546,0.1151,0.2196,0.1879,0.1437,0.2146,0.2360,0.1125,0.0254,0.0285,0.0178,0.0052,0.0081,0.0120,0.0045,0.0121,0.0097,0.0085,0.0047,0.0048,0.0053,R\n",
      "\n",
      "0.0223,0.0375,0.0484,0.0475,0.0647,0.0591,0.0753,0.0098,0.0684,0.1487,0.1156,0.1654,0.3833,0.3598,0.1713,0.1136,0.0349,0.3796,0.7401,0.9925,0.9802,0.8890,0.6712,0.4286,0.3374,0.7366,0.9611,0.7353,0.4856,0.1594,0.3007,0.4096,0.3170,0.3305,0.3408,0.2186,0.2463,0.2726,0.1680,0.2792,0.2558,0.1740,0.2121,0.1099,0.0985,0.1271,0.1459,0.1164,0.0777,0.0439,0.0061,0.0145,0.0128,0.0145,0.0058,0.0049,0.0065,0.0093,0.0059,0.0022,R\n",
      "\n",
      "0.0164,0.0173,0.0347,0.0070,0.0187,0.0671,0.1056,0.0697,0.0962,0.0251,0.0801,0.1056,0.1266,0.0890,0.0198,0.1133,0.2826,0.3234,0.3238,0.4333,0.6068,0.7652,0.9203,0.9719,0.9207,0.7545,0.8289,0.8907,0.7309,0.6896,0.5829,0.4935,0.3101,0.0306,0.0244,0.1108,0.1594,0.1371,0.0696,0.0452,0.0620,0.1421,0.1597,0.1384,0.0372,0.0688,0.0867,0.0513,0.0092,0.0198,0.0118,0.0090,0.0223,0.0179,0.0084,0.0068,0.0032,0.0035,0.0056,0.0040,R\n",
      "\n",
      "0.0039,0.0063,0.0152,0.0336,0.0310,0.0284,0.0396,0.0272,0.0323,0.0452,0.0492,0.0996,0.1424,0.1194,0.0628,0.0907,0.1177,0.1429,0.1223,0.1104,0.1847,0.3715,0.4382,0.5707,0.6654,0.7476,0.7654,0.8555,0.9720,0.9221,0.7502,0.7209,0.7757,0.6055,0.5021,0.4499,0.3947,0.4281,0.4427,0.3749,0.1972,0.0511,0.0793,0.1269,0.1533,0.0690,0.0402,0.0534,0.0228,0.0073,0.0062,0.0062,0.0120,0.0052,0.0056,0.0093,0.0042,0.0003,0.0053,0.0036,R\n",
      "\n",
      "0.0123,0.0309,0.0169,0.0313,0.0358,0.0102,0.0182,0.0579,0.1122,0.0835,0.0548,0.0847,0.2026,0.2557,0.1870,0.2032,0.1463,0.2849,0.5824,0.7728,0.7852,0.8515,0.5312,0.3653,0.5973,0.8275,1.0000,0.8673,0.6301,0.4591,0.3940,0.2576,0.2817,0.2641,0.2757,0.2698,0.3994,0.4576,0.3940,0.2522,0.1782,0.1354,0.0516,0.0337,0.0894,0.0861,0.0872,0.0445,0.0134,0.0217,0.0188,0.0133,0.0265,0.0224,0.0074,0.0118,0.0026,0.0092,0.0009,0.0044,R\n",
      "\n",
      "0.0079,0.0086,0.0055,0.0250,0.0344,0.0546,0.0528,0.0958,0.1009,0.1240,0.1097,0.1215,0.1874,0.3383,0.3227,0.2723,0.3943,0.6432,0.7271,0.8673,0.9674,0.9847,0.9480,0.8036,0.6833,0.5136,0.3090,0.0832,0.4019,0.2344,0.1905,0.1235,0.1717,0.2351,0.2489,0.3649,0.3382,0.1589,0.0989,0.1089,0.1043,0.0839,0.1391,0.0819,0.0678,0.0663,0.1202,0.0692,0.0152,0.0266,0.0174,0.0176,0.0127,0.0088,0.0098,0.0019,0.0059,0.0058,0.0059,0.0032,R\n",
      "\n",
      "0.0090,0.0062,0.0253,0.0489,0.1197,0.1589,0.1392,0.0987,0.0955,0.1895,0.1896,0.2547,0.4073,0.2988,0.2901,0.5326,0.4022,0.1571,0.3024,0.3907,0.3542,0.4438,0.6414,0.4601,0.6009,0.8690,0.8345,0.7669,0.5081,0.4620,0.5380,0.5375,0.3844,0.3601,0.7402,0.7761,0.3858,0.0667,0.3684,0.6114,0.3510,0.2312,0.2195,0.3051,0.1937,0.1570,0.0479,0.0538,0.0146,0.0068,0.0187,0.0059,0.0095,0.0194,0.0080,0.0152,0.0158,0.0053,0.0189,0.0102,R\n",
      "\n",
      "0.0124,0.0433,0.0604,0.0449,0.0597,0.0355,0.0531,0.0343,0.1052,0.2120,0.1640,0.1901,0.3026,0.2019,0.0592,0.2390,0.3657,0.3809,0.5929,0.6299,0.5801,0.4574,0.4449,0.3691,0.6446,0.8940,0.8978,0.4980,0.3333,0.2350,0.1553,0.3666,0.4340,0.3082,0.3024,0.4109,0.5501,0.4129,0.5499,0.5018,0.3132,0.2802,0.2351,0.2298,0.1155,0.0724,0.0621,0.0318,0.0450,0.0167,0.0078,0.0083,0.0057,0.0174,0.0188,0.0054,0.0114,0.0196,0.0147,0.0062,R\n",
      "\n",
      "0.0298,0.0615,0.0650,0.0921,0.1615,0.2294,0.2176,0.2033,0.1459,0.0852,0.2476,0.3645,0.2777,0.2826,0.3237,0.4335,0.5638,0.4555,0.4348,0.6433,0.3932,0.1989,0.3540,0.9165,0.9371,0.4620,0.2771,0.6613,0.8028,0.4200,0.5192,0.6962,0.5792,0.8889,0.7863,0.7133,0.7615,0.4401,0.3009,0.3163,0.2809,0.2898,0.0526,0.1867,0.1553,0.1633,0.1252,0.0748,0.0452,0.0064,0.0154,0.0031,0.0153,0.0071,0.0212,0.0076,0.0152,0.0049,0.0200,0.0073,R\n",
      "\n",
      "0.0352,0.0116,0.0191,0.0469,0.0737,0.1185,0.1683,0.1541,0.1466,0.2912,0.2328,0.2237,0.2470,0.1560,0.3491,0.3308,0.2299,0.2203,0.2493,0.4128,0.3158,0.6191,0.5854,0.3395,0.2561,0.5599,0.8145,0.6941,0.6985,0.8660,0.5930,0.3664,0.6750,0.8697,0.7837,0.7552,0.5789,0.4713,0.1252,0.6087,0.7322,0.5977,0.3431,0.1803,0.2378,0.3424,0.2303,0.0689,0.0216,0.0469,0.0426,0.0346,0.0158,0.0154,0.0109,0.0048,0.0095,0.0015,0.0073,0.0067,R\n",
      "\n",
      "0.0192,0.0607,0.0378,0.0774,0.1388,0.0809,0.0568,0.0219,0.1037,0.1186,0.1237,0.1601,0.3520,0.4479,0.3769,0.5761,0.6426,0.6790,0.7157,0.5466,0.5399,0.6362,0.7849,0.7756,0.5780,0.4862,0.4181,0.2457,0.0716,0.0613,0.1816,0.4493,0.5976,0.3785,0.2495,0.5771,0.8852,0.8409,0.3570,0.3133,0.6096,0.6378,0.2709,0.1419,0.1260,0.1288,0.0790,0.0829,0.0520,0.0216,0.0360,0.0331,0.0131,0.0120,0.0108,0.0024,0.0045,0.0037,0.0112,0.0075,R\n",
      "\n",
      "0.0270,0.0092,0.0145,0.0278,0.0412,0.0757,0.1026,0.1138,0.0794,0.1520,0.1675,0.1370,0.1361,0.1345,0.2144,0.5354,0.6830,0.5600,0.3093,0.3226,0.4430,0.5573,0.5782,0.6173,0.8132,0.9819,0.9823,0.9166,0.7423,0.7736,0.8473,0.7352,0.6671,0.6083,0.6239,0.5972,0.5715,0.5242,0.2924,0.1536,0.2003,0.2031,0.2207,0.1778,0.1353,0.1373,0.0749,0.0472,0.0325,0.0179,0.0045,0.0084,0.0010,0.0018,0.0068,0.0039,0.0120,0.0132,0.0070,0.0088,R\n",
      "\n",
      "0.0126,0.0149,0.0641,0.1732,0.2565,0.2559,0.2947,0.4110,0.4983,0.5920,0.5832,0.5419,0.5472,0.5314,0.4981,0.6985,0.8292,0.7839,0.8215,0.9363,1.0000,0.9224,0.7839,0.5470,0.4562,0.5922,0.5448,0.3971,0.0882,0.2385,0.2005,0.0587,0.2544,0.2009,0.0329,0.1547,0.1212,0.2446,0.3171,0.3195,0.3051,0.0836,0.1266,0.1381,0.1136,0.0516,0.0073,0.0278,0.0372,0.0121,0.0153,0.0092,0.0035,0.0098,0.0121,0.0006,0.0181,0.0094,0.0116,0.0063,R\n",
      "\n",
      "0.0473,0.0509,0.0819,0.1252,0.1783,0.3070,0.3008,0.2362,0.3830,0.3759,0.3021,0.2909,0.2301,0.1411,0.1582,0.2430,0.4474,0.5964,0.6744,0.7969,0.8319,0.7813,0.8626,0.7369,0.4122,0.2596,0.3392,0.3788,0.4488,0.6281,0.7449,0.7328,0.7704,0.7870,0.6048,0.5860,0.6385,0.7279,0.6286,0.5316,0.4069,0.1791,0.1625,0.2527,0.1903,0.1643,0.0604,0.0209,0.0436,0.0175,0.0107,0.0193,0.0118,0.0064,0.0042,0.0054,0.0049,0.0082,0.0028,0.0027,R\n",
      "\n",
      "0.0664,0.0575,0.0842,0.0372,0.0458,0.0771,0.0771,0.1130,0.2353,0.1838,0.2869,0.4129,0.3647,0.1984,0.2840,0.4039,0.5837,0.6792,0.6086,0.4858,0.3246,0.2013,0.2082,0.1686,0.2484,0.2736,0.2984,0.4655,0.6990,0.7474,0.7956,0.7981,0.6715,0.6942,0.7440,0.8169,0.8912,1.0000,0.8753,0.7061,0.6803,0.5898,0.4618,0.3639,0.1492,0.1216,0.1306,0.1198,0.0578,0.0235,0.0135,0.0141,0.0190,0.0043,0.0036,0.0026,0.0024,0.0162,0.0109,0.0079,R\n",
      "\n",
      "0.0099,0.0484,0.0299,0.0297,0.0652,0.1077,0.2363,0.2385,0.0075,0.1882,0.1456,0.1892,0.3176,0.1340,0.2169,0.2458,0.2589,0.2786,0.2298,0.0656,0.1441,0.1179,0.1668,0.1783,0.2476,0.2570,0.1036,0.5356,0.7124,0.6291,0.4756,0.6015,0.7208,0.6234,0.5725,0.7523,0.8712,0.9252,0.9709,0.9297,0.8995,0.7911,0.5600,0.2838,0.4407,0.5507,0.4331,0.2905,0.1981,0.0779,0.0396,0.0173,0.0149,0.0115,0.0202,0.0139,0.0029,0.0160,0.0106,0.0134,R\n",
      "\n",
      "0.0115,0.0150,0.0136,0.0076,0.0211,0.1058,0.1023,0.0440,0.0931,0.0734,0.0740,0.0622,0.1055,0.1183,0.1721,0.2584,0.3232,0.3817,0.4243,0.4217,0.4449,0.4075,0.3306,0.4012,0.4466,0.5218,0.7552,0.9503,1.0000,0.9084,0.8283,0.7571,0.7262,0.6152,0.5680,0.5757,0.5324,0.3672,0.1669,0.0866,0.0646,0.1891,0.2683,0.2887,0.2341,0.1668,0.1015,0.1195,0.0704,0.0167,0.0107,0.0091,0.0016,0.0084,0.0064,0.0026,0.0029,0.0037,0.0070,0.0041,R\n",
      "\n",
      "0.0293,0.0644,0.0390,0.0173,0.0476,0.0816,0.0993,0.0315,0.0736,0.0860,0.0414,0.0472,0.0835,0.0938,0.1466,0.0809,0.1179,0.2179,0.3326,0.3258,0.2111,0.2302,0.3361,0.4259,0.4609,0.2606,0.0874,0.2862,0.5606,0.8344,0.8096,0.7250,0.8048,0.9435,1.0000,0.8960,0.5516,0.3037,0.2338,0.2382,0.3318,0.3821,0.1575,0.2228,0.1582,0.1433,0.1634,0.1133,0.0567,0.0133,0.0170,0.0035,0.0052,0.0083,0.0078,0.0075,0.0105,0.0160,0.0095,0.0011,R\n",
      "\n",
      "0.0201,0.0026,0.0138,0.0062,0.0133,0.0151,0.0541,0.0210,0.0505,0.1097,0.0841,0.0942,0.1204,0.0420,0.0031,0.0162,0.0624,0.2127,0.3436,0.3813,0.3825,0.4764,0.6313,0.7523,0.8675,0.8788,0.7901,0.8357,0.9631,0.9619,0.9236,0.8903,0.9708,0.9647,0.7892,0.5307,0.2718,0.1953,0.1374,0.3105,0.3790,0.4105,0.3355,0.2998,0.2748,0.2024,0.1043,0.0453,0.0337,0.0122,0.0072,0.0108,0.0070,0.0063,0.0030,0.0011,0.0007,0.0024,0.0057,0.0044,R\n",
      "\n",
      "0.0151,0.0320,0.0599,0.1050,0.1163,0.1734,0.1679,0.1119,0.0889,0.1205,0.0847,0.1518,0.2305,0.2793,0.3404,0.4527,0.6950,0.8807,0.9154,0.7542,0.6736,0.7146,0.8335,0.7701,0.6993,0.6543,0.5040,0.4926,0.4992,0.4161,0.1631,0.0404,0.0637,0.2962,0.3609,0.1866,0.0476,0.1497,0.2405,0.1980,0.3175,0.2379,0.1716,0.1559,0.1556,0.0422,0.0493,0.0476,0.0219,0.0059,0.0086,0.0061,0.0015,0.0084,0.0128,0.0054,0.0011,0.0019,0.0023,0.0062,R\n",
      "\n",
      "0.0177,0.0300,0.0288,0.0394,0.0630,0.0526,0.0688,0.0633,0.0624,0.0613,0.1680,0.3476,0.4561,0.5188,0.6308,0.7201,0.5153,0.3818,0.2644,0.3345,0.4865,0.6628,0.7389,0.9213,1.0000,0.7750,0.5593,0.6172,0.8635,0.6592,0.4770,0.4983,0.3330,0.3076,0.2876,0.2226,0.0794,0.0603,0.1049,0.0606,0.1530,0.0983,0.1643,0.1901,0.1107,0.1917,0.1467,0.0392,0.0356,0.0270,0.0168,0.0102,0.0122,0.0044,0.0075,0.0124,0.0099,0.0057,0.0032,0.0019,R\n",
      "\n",
      "0.0100,0.0275,0.0190,0.0371,0.0416,0.0201,0.0314,0.0651,0.1896,0.2668,0.3376,0.3282,0.2432,0.1268,0.1278,0.4441,0.6795,0.7051,0.7966,0.9401,0.9857,0.8193,0.5789,0.6394,0.7043,0.6875,0.4081,0.1811,0.2064,0.3917,0.3791,0.2042,0.2227,0.3341,0.3984,0.5077,0.5534,0.3352,0.2723,0.2278,0.2044,0.1986,0.0835,0.0908,0.1380,0.1948,0.1211,0.0843,0.0589,0.0247,0.0118,0.0088,0.0104,0.0036,0.0088,0.0047,0.0117,0.0020,0.0091,0.0058,R\n",
      "\n",
      "0.0189,0.0308,0.0197,0.0622,0.0080,0.0789,0.1440,0.1451,0.1789,0.2522,0.2607,0.3710,0.3906,0.2672,0.2716,0.4183,0.6988,0.5733,0.2226,0.2631,0.7473,0.7263,0.3393,0.2824,0.6053,0.5897,0.4967,0.8616,0.8339,0.4084,0.2268,0.1745,0.0507,0.1588,0.3040,0.1369,0.1605,0.2061,0.0734,0.0202,0.1638,0.1583,0.1830,0.1886,0.1008,0.0663,0.0183,0.0404,0.0108,0.0143,0.0091,0.0038,0.0096,0.0142,0.0190,0.0140,0.0099,0.0092,0.0052,0.0075,R\n",
      "\n",
      "0.0240,0.0218,0.0324,0.0569,0.0330,0.0513,0.0897,0.0713,0.0569,0.0389,0.1934,0.2434,0.2906,0.2606,0.3811,0.4997,0.3015,0.3655,0.6791,0.7307,0.5053,0.4441,0.6987,0.8133,0.7781,0.8943,0.8929,0.8913,0.8610,0.8063,0.5540,0.2446,0.3459,0.1615,0.2467,0.5564,0.4681,0.0979,0.1582,0.0751,0.3321,0.3745,0.2666,0.1078,0.1418,0.1687,0.0738,0.0634,0.0144,0.0226,0.0061,0.0162,0.0146,0.0093,0.0112,0.0094,0.0054,0.0019,0.0066,0.0023,R\n",
      "\n",
      "0.0084,0.0153,0.0291,0.0432,0.0951,0.0752,0.0414,0.0259,0.0692,0.1753,0.1970,0.1167,0.1683,0.0814,0.2179,0.5121,0.7231,0.7776,0.6222,0.3501,0.3733,0.2622,0.3776,0.7361,0.8673,0.8223,0.7772,0.7862,0.5652,0.3635,0.3534,0.3865,0.3370,0.1693,0.2627,0.3195,0.1388,0.1048,0.1681,0.1910,0.1174,0.0933,0.0856,0.0951,0.0986,0.0956,0.0426,0.0407,0.0106,0.0179,0.0056,0.0236,0.0114,0.0136,0.0117,0.0060,0.0058,0.0031,0.0072,0.0045,R\n",
      "\n",
      "0.0195,0.0213,0.0058,0.0190,0.0319,0.0571,0.1004,0.0668,0.0691,0.0242,0.0728,0.0639,0.3002,0.3854,0.4767,0.4602,0.3175,0.4160,0.6428,1.0000,0.8631,0.5212,0.3156,0.5952,0.7732,0.6042,0.4375,0.5487,0.4720,0.6235,0.3851,0.1590,0.3891,0.5294,0.3504,0.4480,0.4041,0.5031,0.6475,0.5493,0.3548,0.2028,0.1882,0.0845,0.1315,0.1590,0.0562,0.0617,0.0343,0.0370,0.0261,0.0157,0.0074,0.0271,0.0203,0.0089,0.0095,0.0095,0.0021,0.0053,R\n",
      "\n",
      "0.0442,0.0477,0.0049,0.0581,0.0278,0.0678,0.1664,0.1490,0.0974,0.1268,0.1109,0.2375,0.2007,0.2140,0.1109,0.2036,0.2468,0.6682,0.8345,0.8252,0.8017,0.8982,0.9664,0.8515,0.6626,0.3241,0.2054,0.5669,0.5726,0.4877,0.7532,0.7600,0.5185,0.4120,0.5560,0.5569,0.1336,0.3831,0.4611,0.4330,0.2556,0.1466,0.3489,0.2659,0.0944,0.1370,0.1344,0.0416,0.0719,0.0637,0.0210,0.0204,0.0216,0.0135,0.0055,0.0073,0.0080,0.0105,0.0059,0.0105,R\n",
      "\n",
      "0.0311,0.0491,0.0692,0.0831,0.0079,0.0200,0.0981,0.1016,0.2025,0.0767,0.1767,0.2555,0.2812,0.2722,0.3227,0.3463,0.5395,0.7911,0.9064,0.8701,0.7672,0.2957,0.4148,0.6043,0.3178,0.3482,0.6158,0.8049,0.6289,0.4999,0.5830,0.6660,0.4124,0.1260,0.2487,0.4676,0.5382,0.3150,0.2139,0.1848,0.1679,0.2328,0.1015,0.0713,0.0615,0.0779,0.0761,0.0845,0.0592,0.0068,0.0089,0.0087,0.0032,0.0130,0.0188,0.0101,0.0229,0.0182,0.0046,0.0038,R\n",
      "\n",
      "0.0206,0.0132,0.0533,0.0569,0.0647,0.1432,0.1344,0.2041,0.1571,0.1573,0.2327,0.1785,0.1507,0.1916,0.2061,0.2307,0.2360,0.1299,0.3812,0.5858,0.4497,0.4876,1.0000,0.8675,0.4718,0.5341,0.6197,0.7143,0.5605,0.3728,0.2481,0.1921,0.1386,0.3325,0.2883,0.3228,0.2607,0.2040,0.2396,0.1319,0.0683,0.0334,0.0716,0.0976,0.0787,0.0522,0.0500,0.0231,0.0221,0.0144,0.0307,0.0386,0.0147,0.0018,0.0100,0.0096,0.0077,0.0180,0.0109,0.0070,R\n",
      "\n",
      "0.0094,0.0166,0.0398,0.0359,0.0681,0.0706,0.1020,0.0893,0.0381,0.1328,0.1303,0.0273,0.0644,0.0712,0.1204,0.0717,0.1224,0.2349,0.3684,0.3918,0.4925,0.8793,0.9606,0.8786,0.6905,0.6937,0.5674,0.6540,0.7802,0.7575,0.5836,0.6316,0.8108,0.9039,0.8647,0.6695,0.4027,0.2370,0.2685,0.3662,0.3267,0.2200,0.2996,0.2205,0.1163,0.0635,0.0465,0.0422,0.0174,0.0172,0.0134,0.0141,0.0191,0.0145,0.0065,0.0129,0.0217,0.0087,0.0077,0.0122,R\n",
      "\n",
      "0.0333,0.0221,0.0270,0.0481,0.0679,0.0981,0.0843,0.1172,0.0759,0.0920,0.1475,0.0522,0.1119,0.0970,0.1174,0.1678,0.1642,0.1205,0.0494,0.1544,0.3485,0.6146,0.9146,0.9364,0.8677,0.8772,0.8553,0.8833,1.0000,0.8296,0.6601,0.5499,0.5716,0.6859,0.6825,0.5142,0.2750,0.1358,0.1551,0.2646,0.1994,0.1883,0.2746,0.1651,0.0575,0.0695,0.0598,0.0456,0.0021,0.0068,0.0036,0.0022,0.0032,0.0060,0.0054,0.0063,0.0143,0.0132,0.0051,0.0041,R\n",
      "\n",
      "0.0123,0.0022,0.0196,0.0206,0.0180,0.0492,0.0033,0.0398,0.0791,0.0475,0.1152,0.0520,0.1192,0.1943,0.1840,0.2077,0.1956,0.1630,0.1218,0.1017,0.1354,0.3157,0.4645,0.5906,0.6776,0.8119,0.8594,0.9228,0.8387,0.7238,0.6292,0.5181,0.4629,0.5255,0.5147,0.3929,0.1279,0.0411,0.0859,0.1131,0.1306,0.1757,0.2648,0.1955,0.0656,0.0580,0.0319,0.0301,0.0272,0.0074,0.0149,0.0125,0.0134,0.0026,0.0038,0.0018,0.0113,0.0058,0.0047,0.0071,R\n",
      "\n",
      "0.0091,0.0213,0.0206,0.0505,0.0657,0.0795,0.0970,0.0872,0.0743,0.0837,0.1579,0.0898,0.0309,0.1856,0.2969,0.2032,0.1264,0.1655,0.1661,0.2091,0.2310,0.4460,0.6634,0.6933,0.7663,0.8206,0.7049,0.7560,0.7466,0.6387,0.4846,0.3328,0.5356,0.8741,0.8573,0.6718,0.3446,0.3150,0.2702,0.2598,0.2742,0.3594,0.4382,0.2460,0.0758,0.0187,0.0797,0.0748,0.0367,0.0155,0.0300,0.0112,0.0112,0.0102,0.0026,0.0097,0.0098,0.0043,0.0071,0.0108,R\n",
      "\n",
      "0.0068,0.0232,0.0513,0.0444,0.0249,0.0637,0.0422,0.1130,0.1911,0.2475,0.1606,0.0922,0.2398,0.3220,0.4295,0.2652,0.0666,0.1442,0.2373,0.2595,0.2493,0.3903,0.6384,0.8037,0.7026,0.6874,0.6997,0.8558,1.0000,0.9621,0.8996,0.7575,0.6902,0.5686,0.4396,0.4546,0.2959,0.1587,0.1681,0.0842,0.1173,0.1754,0.2728,0.1705,0.0194,0.0213,0.0354,0.0420,0.0093,0.0204,0.0199,0.0173,0.0163,0.0055,0.0045,0.0068,0.0041,0.0052,0.0194,0.0105,R\n",
      "\n",
      "0.0093,0.0185,0.0056,0.0064,0.0260,0.0458,0.0470,0.0057,0.0425,0.0640,0.0888,0.1599,0.1541,0.2768,0.2176,0.2799,0.3491,0.2824,0.2479,0.3005,0.4300,0.4684,0.4520,0.5026,0.6217,0.6571,0.6632,0.7321,0.8534,1.0000,0.8448,0.6354,0.6308,0.6211,0.6976,0.5868,0.4889,0.3683,0.2043,0.1469,0.2220,0.1449,0.1490,0.1211,0.1144,0.0791,0.0365,0.0152,0.0085,0.0120,0.0022,0.0069,0.0064,0.0129,0.0114,0.0054,0.0089,0.0050,0.0058,0.0025,R\n",
      "\n",
      "0.0211,0.0319,0.0415,0.0286,0.0121,0.0438,0.1299,0.1390,0.0695,0.0568,0.0869,0.1935,0.1478,0.1871,0.1994,0.3283,0.6861,0.5814,0.2500,0.1734,0.3363,0.5588,0.6592,0.7012,0.8099,0.8901,0.8745,0.7887,0.8725,0.9376,0.8920,0.7508,0.6832,0.7610,0.9017,1.0000,0.9123,0.7388,0.5915,0.4057,0.3019,0.2331,0.2931,0.2298,0.2391,0.1910,0.1096,0.0300,0.0171,0.0383,0.0053,0.0090,0.0042,0.0153,0.0106,0.0020,0.0105,0.0049,0.0070,0.0080,R\n",
      "\n",
      "0.0093,0.0269,0.0217,0.0339,0.0305,0.1172,0.1450,0.0638,0.0740,0.1360,0.2132,0.3738,0.3738,0.2673,0.2333,0.5367,0.7312,0.7659,0.6271,0.4395,0.4330,0.4326,0.5544,0.7360,0.8589,0.8989,0.9420,0.9401,0.9379,0.8575,0.7284,0.6700,0.7547,0.8773,0.9919,0.9922,0.9419,0.8388,0.6605,0.4816,0.2917,0.1769,0.1136,0.0701,0.1578,0.1938,0.1106,0.0693,0.0176,0.0205,0.0309,0.0212,0.0091,0.0056,0.0086,0.0092,0.0070,0.0116,0.0060,0.0110,R\n",
      "\n",
      "0.0257,0.0447,0.0388,0.0239,0.1315,0.1323,0.1608,0.2145,0.0847,0.0561,0.0891,0.0861,0.1531,0.1524,0.1849,0.2871,0.2009,0.2748,0.5017,0.2172,0.4978,0.5265,0.3647,0.5768,0.5161,0.5715,0.4006,0.3650,0.6685,0.8659,0.8052,0.4082,0.3379,0.5092,0.6776,0.7313,0.6062,0.7040,0.8849,0.8979,0.7751,0.7247,0.7733,0.7762,0.6009,0.4514,0.3096,0.1859,0.0956,0.0206,0.0206,0.0096,0.0153,0.0096,0.0131,0.0198,0.0025,0.0199,0.0255,0.0180,R\n",
      "\n",
      "0.0408,0.0653,0.0397,0.0604,0.0496,0.1817,0.1178,0.1024,0.0583,0.2176,0.2459,0.3332,0.3087,0.2613,0.3232,0.3731,0.4203,0.5364,0.7062,0.8196,0.8835,0.8299,0.7609,0.7605,0.8367,0.8905,0.7652,0.5897,0.3037,0.0823,0.2787,0.7241,0.8032,0.8050,0.7676,0.7468,0.6253,0.1730,0.2916,0.5003,0.5220,0.4824,0.4004,0.3877,0.1651,0.0442,0.0663,0.0418,0.0475,0.0235,0.0066,0.0062,0.0129,0.0184,0.0069,0.0198,0.0199,0.0102,0.0070,0.0055,R\n",
      "\n",
      "0.0308,0.0339,0.0202,0.0889,0.1570,0.1750,0.0920,0.1353,0.1593,0.2795,0.3336,0.2940,0.1608,0.3335,0.4985,0.7295,0.7350,0.8253,0.8793,0.9657,1.0000,0.8707,0.6471,0.5973,0.8218,0.7755,0.6111,0.4195,0.2990,0.1354,0.2438,0.5624,0.5555,0.6963,0.7298,0.7022,0.5468,0.1421,0.4738,0.6410,0.4375,0.3178,0.2377,0.2808,0.1374,0.1136,0.1034,0.0688,0.0422,0.0117,0.0070,0.0167,0.0127,0.0138,0.0090,0.0051,0.0029,0.0122,0.0056,0.0020,R\n",
      "\n",
      "0.0373,0.0281,0.0232,0.0225,0.0179,0.0733,0.0841,0.1031,0.0993,0.0802,0.1564,0.2565,0.2624,0.1179,0.0597,0.1563,0.2241,0.3586,0.1792,0.3256,0.6079,0.6988,0.8391,0.8553,0.7710,0.6215,0.5736,0.4402,0.4056,0.4411,0.5130,0.5965,0.7272,0.6539,0.5902,0.5393,0.4897,0.4081,0.4145,0.6003,0.7196,0.6633,0.6287,0.4087,0.3212,0.2518,0.1482,0.0988,0.0317,0.0269,0.0066,0.0008,0.0045,0.0024,0.0006,0.0073,0.0096,0.0054,0.0085,0.0060,R\n",
      "\n",
      "0.0190,0.0038,0.0642,0.0452,0.0333,0.0690,0.0901,0.1454,0.0740,0.0349,0.1459,0.3473,0.3197,0.2823,0.0166,0.0572,0.2164,0.4563,0.3819,0.5627,0.6484,0.7235,0.8242,0.8766,1.0000,0.8582,0.6563,0.5087,0.4817,0.4530,0.4521,0.4532,0.5385,0.5308,0.5356,0.5271,0.4260,0.2436,0.1205,0.3845,0.4107,0.5067,0.4216,0.2479,0.1586,0.1124,0.0651,0.0789,0.0325,0.0070,0.0026,0.0093,0.0118,0.0112,0.0094,0.0140,0.0072,0.0022,0.0055,0.0122,R\n",
      "\n",
      "0.0119,0.0582,0.0623,0.0600,0.1397,0.1883,0.1422,0.1447,0.0487,0.0864,0.2143,0.3720,0.2665,0.2113,0.1103,0.1136,0.1934,0.4142,0.3279,0.6222,0.7468,0.7676,0.7867,0.8253,1.0000,0.9481,0.7539,0.6008,0.5437,0.5387,0.5619,0.5141,0.6084,0.5621,0.5956,0.6078,0.5025,0.2829,0.0477,0.2811,0.3422,0.5147,0.4372,0.2470,0.1708,0.1343,0.0838,0.0755,0.0304,0.0074,0.0069,0.0025,0.0103,0.0074,0.0123,0.0069,0.0076,0.0073,0.0030,0.0138,R\n",
      "\n",
      "0.0353,0.0713,0.0326,0.0272,0.0370,0.0792,0.1083,0.0687,0.0298,0.0880,0.1078,0.0979,0.2250,0.2819,0.2099,0.1240,0.1699,0.0939,0.1091,0.1410,0.1268,0.3151,0.1430,0.2264,0.5756,0.7876,0.7158,0.5998,0.5583,0.6295,0.7659,0.8940,0.8436,0.6807,0.8380,1.0000,0.9497,0.7866,0.5647,0.3480,0.2585,0.2304,0.2948,0.3363,0.3017,0.2193,0.1316,0.1078,0.0559,0.0035,0.0098,0.0163,0.0242,0.0043,0.0202,0.0108,0.0037,0.0096,0.0093,0.0053,R\n",
      "\n",
      "0.0131,0.0068,0.0308,0.0311,0.0085,0.0767,0.0771,0.0640,0.0726,0.0901,0.0750,0.0844,0.1226,0.1619,0.2317,0.2934,0.3526,0.3657,0.3221,0.3093,0.4084,0.4285,0.4663,0.5956,0.6948,0.8386,0.8875,0.6404,0.3308,0.3425,0.4920,0.4592,0.3034,0.4366,0.5175,0.5122,0.4746,0.4902,0.4603,0.4460,0.4196,0.2873,0.2296,0.0949,0.0095,0.0527,0.0383,0.0107,0.0108,0.0077,0.0109,0.0062,0.0028,0.0040,0.0075,0.0039,0.0053,0.0013,0.0052,0.0023,R\n",
      "\n",
      "0.0087,0.0046,0.0081,0.0230,0.0586,0.0682,0.0993,0.0717,0.0576,0.0818,0.1315,0.1862,0.2789,0.2579,0.2240,0.2568,0.2933,0.2991,0.3924,0.4691,0.5665,0.6464,0.6774,0.7577,0.8856,0.9419,1.0000,0.8564,0.6790,0.5587,0.4147,0.2946,0.2025,0.0688,0.1171,0.2157,0.2216,0.2776,0.2309,0.1444,0.1513,0.1745,0.1756,0.1424,0.0908,0.0138,0.0469,0.0480,0.0159,0.0045,0.0015,0.0052,0.0038,0.0079,0.0114,0.0050,0.0030,0.0064,0.0058,0.0030,R\n",
      "\n",
      "0.0293,0.0378,0.0257,0.0062,0.0130,0.0612,0.0895,0.1107,0.0973,0.0751,0.0528,0.1209,0.1763,0.2039,0.2727,0.2321,0.2676,0.2934,0.3295,0.4910,0.5402,0.6257,0.6826,0.7527,0.8504,0.8938,0.9928,0.9134,0.7080,0.6318,0.6126,0.4638,0.2797,0.1721,0.1665,0.2561,0.2735,0.3209,0.2724,0.1880,0.1552,0.2522,0.2121,0.1801,0.1473,0.0681,0.1091,0.0919,0.0397,0.0093,0.0076,0.0065,0.0072,0.0108,0.0051,0.0102,0.0041,0.0055,0.0050,0.0087,R\n",
      "\n",
      "0.0132,0.0080,0.0188,0.0141,0.0436,0.0668,0.0609,0.0131,0.0899,0.0922,0.1445,0.1475,0.2087,0.2558,0.2603,0.1985,0.2394,0.3134,0.4077,0.4529,0.4893,0.5666,0.6234,0.6741,0.8282,0.8823,0.9196,0.8965,0.7549,0.6736,0.6463,0.5007,0.3663,0.2298,0.1362,0.2123,0.2395,0.2673,0.2865,0.2060,0.1659,0.2633,0.2552,0.1696,0.1467,0.1286,0.0926,0.0716,0.0325,0.0258,0.0136,0.0044,0.0028,0.0021,0.0022,0.0048,0.0138,0.0140,0.0028,0.0064,R\n",
      "\n",
      "0.0201,0.0116,0.0123,0.0245,0.0547,0.0208,0.0891,0.0836,0.1335,0.1199,0.1742,0.1387,0.2042,0.2580,0.2616,0.2097,0.2532,0.3213,0.4327,0.4760,0.5328,0.6057,0.6696,0.7476,0.8930,0.9405,1.0000,0.9785,0.8473,0.7639,0.6701,0.4989,0.3718,0.2196,0.1416,0.2680,0.2630,0.3104,0.3392,0.2123,0.1170,0.2655,0.2203,0.1541,0.1464,0.1044,0.1225,0.0745,0.0490,0.0224,0.0032,0.0076,0.0045,0.0056,0.0075,0.0037,0.0045,0.0029,0.0008,0.0018,R\n",
      "\n",
      "0.0152,0.0102,0.0113,0.0263,0.0097,0.0391,0.0857,0.0915,0.0949,0.1504,0.1911,0.2115,0.2249,0.2573,0.1701,0.2023,0.2538,0.3417,0.4026,0.4553,0.5525,0.5991,0.5854,0.7114,0.9500,0.9858,1.0000,0.9578,0.8642,0.7128,0.5893,0.4323,0.2897,0.1744,0.0770,0.2297,0.2459,0.3101,0.3312,0.2220,0.0871,0.2064,0.1808,0.1624,0.1120,0.0815,0.1117,0.0950,0.0412,0.0120,0.0048,0.0049,0.0041,0.0036,0.0013,0.0046,0.0037,0.0011,0.0034,0.0033,R\n",
      "\n",
      "0.0216,0.0124,0.0174,0.0152,0.0608,0.1026,0.1139,0.0877,0.1160,0.0866,0.1564,0.0780,0.0997,0.0915,0.0662,0.1134,0.1740,0.2573,0.3294,0.3910,0.5438,0.6115,0.7022,0.7610,0.7973,0.9105,0.8807,0.7949,0.7990,0.7180,0.6407,0.6312,0.5929,0.6168,0.6498,0.6764,0.6253,0.5117,0.3890,0.3273,0.2509,0.1530,0.1323,0.1657,0.1215,0.0978,0.0452,0.0273,0.0179,0.0092,0.0018,0.0052,0.0049,0.0096,0.0134,0.0122,0.0047,0.0018,0.0006,0.0023,R\n",
      "\n",
      "0.0225,0.0019,0.0075,0.0097,0.0445,0.0906,0.0889,0.0655,0.1624,0.1452,0.1442,0.0948,0.0618,0.1641,0.0708,0.0844,0.2590,0.2679,0.3094,0.4678,0.5958,0.7245,0.8773,0.9214,0.9282,0.9942,1.0000,0.9071,0.8545,0.7293,0.6499,0.6071,0.5588,0.5967,0.6275,0.5459,0.4786,0.3965,0.2087,0.1651,0.1836,0.0652,0.0758,0.0486,0.0353,0.0297,0.0241,0.0379,0.0119,0.0073,0.0051,0.0034,0.0129,0.0100,0.0044,0.0057,0.0030,0.0035,0.0021,0.0027,R\n",
      "\n",
      "0.0125,0.0152,0.0218,0.0175,0.0362,0.0696,0.0873,0.0616,0.1252,0.1302,0.0888,0.0500,0.0628,0.1274,0.0801,0.0742,0.2048,0.2950,0.3193,0.4567,0.5959,0.7101,0.8225,0.8425,0.9065,0.9802,1.0000,0.8752,0.7583,0.6616,0.5786,0.5128,0.4776,0.4994,0.5197,0.5071,0.4577,0.3505,0.1845,0.1890,0.1967,0.1041,0.0550,0.0492,0.0622,0.0505,0.0247,0.0219,0.0102,0.0047,0.0019,0.0041,0.0074,0.0030,0.0050,0.0048,0.0017,0.0041,0.0086,0.0058,R\n",
      "\n",
      "0.0130,0.0006,0.0088,0.0456,0.0525,0.0778,0.0931,0.0941,0.1711,0.1483,0.1532,0.1100,0.0890,0.1236,0.1197,0.1145,0.2137,0.2838,0.3640,0.5430,0.6673,0.7979,0.9273,0.9027,0.9192,1.0000,0.9821,0.9092,0.8184,0.6962,0.5900,0.5447,0.5142,0.5389,0.5531,0.5318,0.4826,0.3790,0.1831,0.1750,0.1679,0.0674,0.0609,0.0375,0.0533,0.0278,0.0179,0.0114,0.0073,0.0116,0.0092,0.0078,0.0041,0.0013,0.0011,0.0045,0.0039,0.0022,0.0023,0.0016,R\n",
      "\n",
      "0.0135,0.0045,0.0051,0.0289,0.0561,0.0929,0.1031,0.0883,0.1596,0.1908,0.1576,0.1112,0.1197,0.1174,0.1415,0.2215,0.2658,0.2713,0.3862,0.5717,0.6797,0.8747,1.0000,0.8948,0.8420,0.9174,0.9307,0.9050,0.8228,0.6986,0.5831,0.4924,0.4563,0.5159,0.5670,0.5284,0.5144,0.3742,0.2282,0.1193,0.1088,0.0431,0.1070,0.0583,0.0046,0.0473,0.0408,0.0290,0.0192,0.0094,0.0025,0.0037,0.0084,0.0102,0.0096,0.0024,0.0037,0.0028,0.0030,0.0030,R\n",
      "\n",
      "0.0086,0.0215,0.0242,0.0445,0.0667,0.0771,0.0499,0.0906,0.1229,0.1185,0.0775,0.1101,0.1042,0.0853,0.0456,0.1304,0.2690,0.2947,0.3669,0.4948,0.6275,0.8162,0.9237,0.8710,0.8052,0.8756,1.0000,0.9858,0.9427,0.8114,0.6987,0.6810,0.6591,0.6954,0.7290,0.6680,0.5917,0.4899,0.3439,0.2366,0.1716,0.1013,0.0766,0.0845,0.0260,0.0333,0.0205,0.0309,0.0101,0.0095,0.0047,0.0072,0.0054,0.0022,0.0016,0.0029,0.0058,0.0050,0.0024,0.0030,R\n",
      "\n",
      "0.0067,0.0096,0.0024,0.0058,0.0197,0.0618,0.0432,0.0951,0.0836,0.1180,0.0978,0.0909,0.0656,0.0593,0.0832,0.1297,0.2038,0.3811,0.4451,0.5224,0.5911,0.6566,0.6308,0.5998,0.4958,0.5647,0.6906,0.8513,1.0000,0.9166,0.7676,0.6177,0.5468,0.5516,0.5463,0.5515,0.4561,0.3466,0.3384,0.2853,0.2502,0.1641,0.1605,0.1491,0.1326,0.0687,0.0602,0.0561,0.0306,0.0154,0.0029,0.0048,0.0023,0.0020,0.0040,0.0019,0.0034,0.0034,0.0051,0.0031,R\n",
      "\n",
      "0.0071,0.0103,0.0135,0.0494,0.0253,0.0806,0.0701,0.0738,0.0117,0.0898,0.0289,0.1554,0.1437,0.1035,0.1424,0.1227,0.0892,0.2047,0.0827,0.1524,0.3031,0.1608,0.0667,0.1426,0.0395,0.1653,0.3399,0.4855,0.5206,0.5508,0.6102,0.5989,0.6764,0.8897,1.0000,0.9517,0.8459,0.7073,0.6697,0.6326,0.5102,0.4161,0.2816,0.1705,0.1421,0.0971,0.0879,0.0863,0.0355,0.0233,0.0252,0.0043,0.0048,0.0076,0.0124,0.0105,0.0054,0.0032,0.0073,0.0063,R\n",
      "\n",
      "0.0176,0.0172,0.0501,0.0285,0.0262,0.0351,0.0362,0.0535,0.0258,0.0474,0.0526,0.1854,0.1040,0.0948,0.0912,0.1688,0.1568,0.0375,0.1316,0.2086,0.1976,0.0946,0.1965,0.1242,0.0616,0.2141,0.4642,0.6471,0.6340,0.6107,0.7046,0.5376,0.5934,0.8443,0.9481,0.9705,0.7766,0.6313,0.5760,0.6148,0.5450,0.4813,0.3406,0.1916,0.1134,0.0640,0.0911,0.0980,0.0563,0.0187,0.0088,0.0042,0.0175,0.0171,0.0079,0.0050,0.0112,0.0179,0.0294,0.0063,R\n",
      "\n",
      "0.0265,0.0440,0.0137,0.0084,0.0305,0.0438,0.0341,0.0780,0.0844,0.0779,0.0327,0.2060,0.1908,0.1065,0.1457,0.2232,0.2070,0.1105,0.1078,0.1165,0.2224,0.0689,0.2060,0.2384,0.0904,0.2278,0.5872,0.8457,0.8467,0.7679,0.8055,0.6260,0.6545,0.8747,0.9885,0.9348,0.6960,0.5733,0.5872,0.6663,0.5651,0.5247,0.3684,0.1997,0.1512,0.0508,0.0931,0.0982,0.0524,0.0188,0.0100,0.0038,0.0187,0.0156,0.0068,0.0097,0.0073,0.0081,0.0086,0.0095,R\n",
      "\n",
      "0.0368,0.0403,0.0317,0.0293,0.0820,0.1342,0.1161,0.0663,0.0155,0.0506,0.0906,0.2545,0.1464,0.1272,0.1223,0.1669,0.1424,0.1285,0.1857,0.1136,0.2069,0.0219,0.2400,0.2547,0.0240,0.1923,0.4753,0.7003,0.6825,0.6443,0.7063,0.5373,0.6601,0.8708,0.9518,0.9605,0.7712,0.6772,0.6431,0.6720,0.6035,0.5155,0.3802,0.2278,0.1522,0.0801,0.0804,0.0752,0.0566,0.0175,0.0058,0.0091,0.0160,0.0160,0.0081,0.0070,0.0135,0.0067,0.0078,0.0068,R\n",
      "\n",
      "0.0195,0.0142,0.0181,0.0406,0.0391,0.0249,0.0892,0.0973,0.0840,0.1191,0.1522,0.1322,0.1434,0.1244,0.0653,0.0890,0.1226,0.1846,0.3880,0.3658,0.2297,0.2610,0.4193,0.5848,0.5643,0.5448,0.4772,0.6897,0.9797,1.0000,0.9546,0.8835,0.7662,0.6547,0.5447,0.4593,0.4679,0.1987,0.0699,0.1493,0.1713,0.1654,0.2600,0.3846,0.3754,0.2414,0.1077,0.0224,0.0155,0.0187,0.0125,0.0028,0.0067,0.0120,0.0012,0.0022,0.0058,0.0042,0.0067,0.0012,R\n",
      "\n",
      "0.0216,0.0215,0.0273,0.0139,0.0357,0.0785,0.0906,0.0908,0.1151,0.0973,0.1203,0.1102,0.1192,0.1762,0.2390,0.2138,0.1929,0.1765,0.0746,0.1265,0.2005,0.1571,0.2605,0.5386,0.8440,1.0000,0.8684,0.6742,0.5537,0.4638,0.3609,0.2055,0.1620,0.2092,0.3100,0.2344,0.1058,0.0383,0.0528,0.1291,0.2241,0.1915,0.1587,0.0942,0.0840,0.0670,0.0342,0.0469,0.0357,0.0136,0.0082,0.0140,0.0044,0.0052,0.0073,0.0021,0.0047,0.0024,0.0009,0.0017,R\n",
      "\n",
      "0.0065,0.0122,0.0068,0.0108,0.0217,0.0284,0.0527,0.0575,0.1054,0.1109,0.0937,0.0827,0.0920,0.0911,0.1487,0.1666,0.1268,0.1374,0.1095,0.1286,0.2146,0.2889,0.4238,0.6168,0.8167,0.9622,0.8280,0.5816,0.4667,0.3539,0.2727,0.1410,0.1863,0.2176,0.2360,0.1725,0.0589,0.0621,0.1847,0.2452,0.2984,0.3041,0.2275,0.1480,0.1102,0.1178,0.0608,0.0333,0.0276,0.0100,0.0023,0.0069,0.0025,0.0027,0.0052,0.0036,0.0026,0.0036,0.0006,0.0035,R\n",
      "\n",
      "0.0036,0.0078,0.0092,0.0387,0.0530,0.1197,0.1243,0.1026,0.1239,0.0888,0.0937,0.1245,0.1599,0.1542,0.1846,0.1732,0.1477,0.1748,0.1455,0.1579,0.2257,0.1975,0.3368,0.5828,0.8505,1.0000,0.8457,0.6624,0.5564,0.3925,0.3233,0.2054,0.1920,0.2227,0.3147,0.2268,0.0795,0.0748,0.1166,0.1969,0.2619,0.2507,0.1983,0.0948,0.0931,0.0965,0.0381,0.0435,0.0336,0.0055,0.0079,0.0119,0.0055,0.0035,0.0036,0.0004,0.0018,0.0049,0.0024,0.0016,R\n",
      "\n",
      "0.0208,0.0186,0.0131,0.0211,0.0610,0.0613,0.0612,0.0506,0.0989,0.1093,0.1063,0.1179,0.1291,0.1591,0.1680,0.1918,0.1615,0.1647,0.1397,0.1426,0.2429,0.2816,0.4290,0.6443,0.9061,1.0000,0.8087,0.6119,0.5260,0.3677,0.2746,0.1020,0.1339,0.1582,0.1952,0.1787,0.0429,0.1096,0.1762,0.2481,0.3150,0.2920,0.1902,0.0696,0.0758,0.0910,0.0441,0.0244,0.0265,0.0095,0.0140,0.0074,0.0063,0.0081,0.0087,0.0044,0.0028,0.0019,0.0049,0.0023,R\n",
      "\n",
      "0.0139,0.0222,0.0089,0.0108,0.0215,0.0136,0.0659,0.0954,0.0786,0.1015,0.1261,0.0828,0.0493,0.0848,0.1514,0.1396,0.1066,0.1923,0.2991,0.3247,0.3797,0.5658,0.7483,0.8757,0.9048,0.7511,0.6858,0.7043,0.5864,0.3773,0.2206,0.2628,0.2672,0.2907,0.1982,0.2288,0.3186,0.2871,0.2921,0.2806,0.2682,0.2112,0.1513,0.1789,0.1850,0.1717,0.0898,0.0656,0.0445,0.0110,0.0024,0.0062,0.0072,0.0113,0.0012,0.0022,0.0025,0.0059,0.0039,0.0048,R\n",
      "\n",
      "0.0109,0.0093,0.0121,0.0378,0.0679,0.0863,0.1004,0.0664,0.0941,0.1036,0.0972,0.0501,0.1546,0.3404,0.4804,0.6570,0.7738,0.7827,0.8152,0.8129,0.8297,0.8535,0.8870,0.8894,0.8980,0.9667,1.0000,0.9134,0.6762,0.4659,0.2895,0.2959,0.1746,0.2112,0.2569,0.2276,0.2149,0.1601,0.0371,0.0117,0.0488,0.0288,0.0597,0.0431,0.0369,0.0025,0.0327,0.0257,0.0182,0.0108,0.0124,0.0077,0.0023,0.0117,0.0053,0.0077,0.0076,0.0056,0.0055,0.0039,R\n",
      "\n",
      "0.0202,0.0104,0.0325,0.0239,0.0807,0.1529,0.1154,0.0608,0.1317,0.1370,0.0843,0.0269,0.1254,0.3046,0.5584,0.7973,0.8341,0.8057,0.8616,0.8769,0.9413,0.9403,0.9409,1.0000,0.9725,0.9309,0.9351,0.7317,0.4421,0.3244,0.4161,0.4611,0.4031,0.3000,0.2459,0.1348,0.2541,0.2255,0.1598,0.1485,0.0845,0.0569,0.0855,0.1262,0.1153,0.0570,0.0426,0.0425,0.0235,0.0006,0.0188,0.0127,0.0081,0.0067,0.0043,0.0065,0.0049,0.0054,0.0073,0.0054,R\n",
      "\n",
      "0.0239,0.0189,0.0466,0.0440,0.0657,0.0742,0.1380,0.1099,0.1384,0.1376,0.0938,0.0259,0.1499,0.2851,0.5743,0.8278,0.8669,0.8131,0.9045,0.9046,1.0000,0.9976,0.9872,0.9761,0.9009,0.9724,0.9675,0.7633,0.4434,0.3822,0.4727,0.4007,0.3381,0.3172,0.2222,0.0733,0.2692,0.1888,0.0712,0.1062,0.0694,0.0300,0.0893,0.1459,0.1348,0.0391,0.0546,0.0469,0.0201,0.0095,0.0155,0.0091,0.0151,0.0080,0.0018,0.0078,0.0045,0.0026,0.0036,0.0024,R\n",
      "\n",
      "0.0336,0.0294,0.0476,0.0539,0.0794,0.0804,0.1136,0.1228,0.1235,0.0842,0.0357,0.0689,0.1705,0.3257,0.4602,0.6225,0.7327,0.7843,0.7988,0.8261,1.0000,0.9814,0.9620,0.9601,0.9118,0.9086,0.7931,0.5877,0.3474,0.4235,0.4633,0.3410,0.2849,0.2847,0.1742,0.0549,0.1192,0.1154,0.0855,0.1811,0.1264,0.0799,0.0378,0.1268,0.1125,0.0505,0.0949,0.0677,0.0259,0.0170,0.0033,0.0150,0.0111,0.0032,0.0035,0.0169,0.0137,0.0015,0.0069,0.0051,R\n",
      "\n",
      "0.0231,0.0351,0.0030,0.0304,0.0339,0.0860,0.1738,0.1351,0.1063,0.0347,0.0575,0.1382,0.2274,0.4038,0.5223,0.6847,0.7521,0.7760,0.7708,0.8627,1.0000,0.8873,0.8057,0.8760,0.9066,0.9430,0.8846,0.6500,0.2970,0.2423,0.2992,0.2285,0.2277,0.1529,0.1037,0.0352,0.1073,0.1373,0.1331,0.1454,0.1115,0.0440,0.0762,0.1381,0.0831,0.0654,0.0844,0.0595,0.0497,0.0313,0.0154,0.0106,0.0097,0.0022,0.0052,0.0072,0.0056,0.0038,0.0043,0.0030,R\n",
      "\n",
      "0.0108,0.0086,0.0058,0.0460,0.0752,0.0887,0.1015,0.0494,0.0472,0.0393,0.1106,0.1412,0.2202,0.2976,0.4116,0.4754,0.5390,0.6279,0.7060,0.7918,0.9493,1.0000,0.9645,0.9432,0.8658,0.7895,0.6501,0.4492,0.4739,0.6153,0.4929,0.3195,0.3735,0.3336,0.1052,0.0671,0.0379,0.0461,0.1694,0.2169,0.1677,0.0644,0.0159,0.0778,0.0653,0.0210,0.0509,0.0387,0.0262,0.0101,0.0161,0.0029,0.0078,0.0114,0.0083,0.0058,0.0003,0.0023,0.0026,0.0027,R\n",
      "\n",
      "0.0229,0.0369,0.0040,0.0375,0.0455,0.1452,0.2211,0.1188,0.0750,0.1631,0.2709,0.3358,0.4091,0.4400,0.5485,0.7213,0.8137,0.9185,1.0000,0.9418,0.9116,0.9349,0.7484,0.5146,0.4106,0.3443,0.6981,0.8713,0.9013,0.8014,0.4380,0.1319,0.1709,0.2484,0.3044,0.2312,0.1338,0.2056,0.2474,0.2790,0.1610,0.0056,0.0351,0.1148,0.1331,0.0276,0.0763,0.0631,0.0309,0.0240,0.0115,0.0064,0.0022,0.0122,0.0151,0.0056,0.0026,0.0029,0.0104,0.0163,R\n",
      "\n",
      "0.0100,0.0194,0.0155,0.0489,0.0839,0.1009,0.1627,0.2071,0.2696,0.2990,0.3242,0.3565,0.3951,0.5201,0.6953,0.8468,1.0000,0.9278,0.8510,0.8010,0.8142,0.8825,0.7302,0.6107,0.7159,0.8458,0.6319,0.4808,0.6291,0.7152,0.6005,0.4235,0.4106,0.3992,0.1730,0.1975,0.2370,0.1339,0.1583,0.3151,0.1968,0.2054,0.1272,0.1129,0.1946,0.2195,0.1930,0.1498,0.0773,0.0196,0.0122,0.0130,0.0073,0.0077,0.0075,0.0060,0.0080,0.0019,0.0053,0.0019,R\n",
      "\n",
      "0.0409,0.0421,0.0573,0.0130,0.0183,0.1019,0.1054,0.1070,0.2302,0.2259,0.2373,0.3323,0.3827,0.4840,0.6812,0.7555,0.9522,0.9826,0.8871,0.8268,0.7561,0.8217,0.6967,0.6444,0.6948,0.8014,0.6053,0.6084,0.8877,0.8557,0.5563,0.2897,0.3638,0.4786,0.2908,0.0899,0.2043,0.1707,0.0407,0.1286,0.1581,0.2191,0.1701,0.0971,0.2217,0.2732,0.1874,0.1062,0.0665,0.0405,0.0113,0.0028,0.0036,0.0105,0.0120,0.0087,0.0061,0.0061,0.0030,0.0078,R\n",
      "\n",
      "0.0217,0.0340,0.0392,0.0236,0.1081,0.1164,0.1398,0.1009,0.1147,0.1777,0.4079,0.4113,0.3973,0.5078,0.6509,0.8073,0.9819,1.0000,0.9407,0.8452,0.8106,0.8460,0.6212,0.5815,0.7745,0.8204,0.5601,0.2989,0.5009,0.6628,0.5753,0.4055,0.3746,0.3481,0.1580,0.1422,0.2130,0.1866,0.1003,0.2396,0.2241,0.2029,0.0710,0.1606,0.1669,0.1700,0.1829,0.1403,0.0506,0.0224,0.0095,0.0031,0.0103,0.0078,0.0077,0.0094,0.0031,0.0030,0.0013,0.0069,R\n",
      "\n",
      "0.0378,0.0318,0.0423,0.0350,0.1787,0.1635,0.0887,0.0817,0.1779,0.2053,0.3135,0.3118,0.3686,0.3885,0.5850,0.7868,0.9739,1.0000,0.9843,0.8610,0.8443,0.9061,0.5847,0.4033,0.5946,0.6793,0.6389,0.5002,0.5578,0.4831,0.4729,0.3318,0.3969,0.3894,0.2314,0.1036,0.1312,0.0864,0.2569,0.3179,0.2649,0.2714,0.1713,0.0584,0.1230,0.2200,0.2198,0.1074,0.0423,0.0162,0.0093,0.0046,0.0044,0.0078,0.0102,0.0065,0.0061,0.0062,0.0043,0.0053,R\n",
      "\n",
      "0.0365,0.1632,0.1636,0.1421,0.1130,0.1306,0.2112,0.2268,0.2992,0.3735,0.3042,0.0387,0.2679,0.5397,0.6204,0.7257,0.8350,0.6888,0.4450,0.3921,0.5605,0.7545,0.8311,1.0000,0.8762,0.7092,0.7009,0.5014,0.3942,0.4456,0.4072,0.0773,0.1423,0.0401,0.3597,0.6847,0.7076,0.3597,0.0612,0.3027,0.3966,0.3868,0.2380,0.2059,0.2288,0.1704,0.1587,0.1792,0.1022,0.0151,0.0223,0.0110,0.0071,0.0205,0.0164,0.0063,0.0078,0.0094,0.0110,0.0068,R\n",
      "\n",
      "0.0188,0.0370,0.0953,0.0824,0.0249,0.0488,0.1424,0.1972,0.1873,0.1806,0.2139,0.1523,0.1975,0.4844,0.7298,0.7807,0.7906,0.6122,0.4200,0.2807,0.5148,0.7569,0.8596,1.0000,0.8457,0.6797,0.6971,0.5843,0.4772,0.5201,0.4241,0.1592,0.1668,0.0588,0.3967,0.7147,0.7319,0.3509,0.0589,0.2690,0.4200,0.3874,0.2440,0.2000,0.2307,0.1886,0.1960,0.1701,0.1366,0.0398,0.0143,0.0093,0.0033,0.0113,0.0030,0.0057,0.0090,0.0057,0.0068,0.0024,R\n",
      "\n",
      "0.0856,0.0454,0.0382,0.0203,0.0385,0.0534,0.2140,0.3110,0.2837,0.2751,0.2707,0.0946,0.1020,0.4519,0.6737,0.6699,0.7066,0.5632,0.3785,0.2721,0.5297,0.7697,0.8643,0.9304,0.9372,0.6247,0.6024,0.6810,0.5047,0.5775,0.4754,0.2400,0.2779,0.1997,0.5305,0.7409,0.7775,0.4424,0.1416,0.3508,0.4482,0.4208,0.3054,0.2235,0.2611,0.2798,0.2392,0.2021,0.1326,0.0358,0.0128,0.0172,0.0138,0.0079,0.0037,0.0051,0.0258,0.0102,0.0037,0.0037,R\n",
      "\n",
      "0.0274,0.0242,0.0621,0.0560,0.1129,0.0973,0.1823,0.1745,0.1440,0.1808,0.2366,0.0906,0.1749,0.4012,0.5187,0.7312,0.9062,0.9260,0.7434,0.4463,0.5103,0.6952,0.7755,0.8364,0.7283,0.6399,0.5759,0.4146,0.3495,0.4437,0.2665,0.2024,0.1942,0.0765,0.3725,0.5843,0.4827,0.2347,0.0999,0.3244,0.3990,0.2975,0.1684,0.1761,0.1683,0.0729,0.1190,0.1297,0.0748,0.0067,0.0255,0.0113,0.0108,0.0085,0.0047,0.0074,0.0104,0.0161,0.0220,0.0173,R\n",
      "\n",
      "0.0235,0.0291,0.0749,0.0519,0.0227,0.0834,0.0677,0.2002,0.2876,0.3674,0.2974,0.0837,0.1912,0.5040,0.6352,0.6804,0.7505,0.6595,0.4509,0.2964,0.4019,0.6794,0.8297,1.0000,0.8240,0.7115,0.7726,0.6124,0.4936,0.5648,0.4906,0.1820,0.1811,0.1107,0.4603,0.6650,0.6423,0.2166,0.1951,0.4947,0.4925,0.4041,0.2402,0.1392,0.1779,0.1946,0.1723,0.1522,0.0929,0.0179,0.0242,0.0083,0.0037,0.0095,0.0105,0.0030,0.0132,0.0068,0.0108,0.0090,R\n",
      "\n",
      "0.0126,0.0519,0.0621,0.0518,0.1072,0.2587,0.2304,0.2067,0.3416,0.4284,0.3015,0.1207,0.3299,0.5707,0.6962,0.9751,1.0000,0.9293,0.6210,0.4586,0.5001,0.5032,0.7082,0.8420,0.8109,0.7690,0.8105,0.6203,0.2356,0.2595,0.6299,0.6762,0.2903,0.4393,0.8529,0.7180,0.4801,0.5856,0.4993,0.2866,0.0601,0.1167,0.2737,0.2812,0.2078,0.0660,0.0491,0.0345,0.0172,0.0287,0.0027,0.0208,0.0048,0.0199,0.0126,0.0022,0.0037,0.0034,0.0114,0.0077,R\n",
      "\n",
      "0.0253,0.0808,0.0507,0.0244,0.1724,0.3823,0.3729,0.3583,0.3429,0.2197,0.2653,0.3223,0.5582,0.6916,0.7943,0.7152,0.3512,0.2008,0.2676,0.4299,0.5280,0.3489,0.1430,0.5453,0.6338,0.7712,0.6838,0.8015,0.8073,0.8310,0.7792,0.5049,0.1413,0.2767,0.5084,0.4787,0.1356,0.2299,0.2789,0.3833,0.2933,0.1155,0.1705,0.1294,0.0909,0.0800,0.0567,0.0198,0.0114,0.0151,0.0085,0.0178,0.0073,0.0079,0.0038,0.0116,0.0033,0.0039,0.0081,0.0053,R\n",
      "\n",
      "0.0260,0.0192,0.0254,0.0061,0.0352,0.0701,0.1263,0.1080,0.1523,0.1630,0.1030,0.2187,0.1542,0.2630,0.2940,0.2978,0.0699,0.1401,0.2990,0.3915,0.3598,0.2403,0.4208,0.5675,0.6094,0.6323,0.6549,0.7673,1.0000,0.8463,0.5509,0.4444,0.5169,0.4268,0.1802,0.0791,0.0535,0.1906,0.2561,0.2153,0.2769,0.2841,0.1733,0.0815,0.0335,0.0933,0.1018,0.0309,0.0208,0.0318,0.0132,0.0118,0.0120,0.0051,0.0070,0.0015,0.0035,0.0008,0.0044,0.0077,R\n",
      "\n",
      "0.0459,0.0437,0.0347,0.0456,0.0067,0.0890,0.1798,0.1741,0.1598,0.1408,0.2693,0.3259,0.4545,0.5785,0.4471,0.2231,0.2164,0.3201,0.2915,0.4235,0.4460,0.2380,0.6415,0.8966,0.8918,0.7529,0.6838,0.8390,1.0000,0.8362,0.5427,0.4577,0.8067,0.6973,0.3915,0.1558,0.1598,0.2161,0.5178,0.4782,0.2344,0.3599,0.2785,0.1807,0.0352,0.0473,0.0322,0.0408,0.0163,0.0088,0.0121,0.0067,0.0032,0.0109,0.0164,0.0151,0.0070,0.0085,0.0117,0.0056,R\n",
      "\n",
      "0.0025,0.0309,0.0171,0.0228,0.0434,0.1224,0.1947,0.1661,0.1368,0.1430,0.0994,0.2250,0.2444,0.3239,0.3039,0.2410,0.0367,0.1672,0.3038,0.4069,0.3613,0.1994,0.4611,0.6849,0.7272,0.7152,0.7102,0.8516,1.0000,0.7690,0.4841,0.3717,0.6096,0.5110,0.2586,0.0916,0.0947,0.2287,0.3480,0.2095,0.1901,0.2941,0.2211,0.1524,0.0746,0.0606,0.0692,0.0446,0.0344,0.0082,0.0108,0.0149,0.0077,0.0036,0.0114,0.0085,0.0101,0.0016,0.0028,0.0014,R\n",
      "\n",
      "0.0291,0.0400,0.0771,0.0809,0.0521,0.1051,0.0145,0.0674,0.1294,0.1146,0.0942,0.0794,0.0252,0.1191,0.1045,0.2050,0.1556,0.2690,0.3784,0.4024,0.3470,0.1395,0.1208,0.2827,0.1500,0.2626,0.4468,0.7520,0.9036,0.7812,0.4766,0.2483,0.5372,0.6279,0.3647,0.4572,0.6359,0.6474,0.5520,0.3253,0.2292,0.0653,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0056,0.0237,0.0204,0.0050,0.0137,0.0164,0.0081,0.0139,0.0111,R\n",
      "\n",
      "0.0181,0.0146,0.0026,0.0141,0.0421,0.0473,0.0361,0.0741,0.1398,0.1045,0.0904,0.0671,0.0997,0.1056,0.0346,0.1231,0.1626,0.3652,0.3262,0.2995,0.2109,0.2104,0.2085,0.2282,0.0747,0.1969,0.4086,0.6385,0.7970,0.7508,0.5517,0.2214,0.4672,0.4479,0.2297,0.3235,0.4480,0.5581,0.6520,0.5354,0.2478,0.2268,0.1788,0.0898,0.0536,0.0374,0.0990,0.0956,0.0317,0.0142,0.0076,0.0223,0.0255,0.0145,0.0233,0.0041,0.0018,0.0048,0.0089,0.0085,R\n",
      "\n",
      "0.0491,0.0279,0.0592,0.1270,0.1772,0.1908,0.2217,0.0768,0.1246,0.2028,0.0947,0.2497,0.2209,0.3195,0.3340,0.3323,0.2780,0.2975,0.2948,0.1729,0.3264,0.3834,0.3523,0.5410,0.5228,0.4475,0.5340,0.5323,0.3907,0.3456,0.4091,0.4639,0.5580,0.5727,0.6355,0.7563,0.6903,0.6176,0.5379,0.5622,0.6508,0.4797,0.3736,0.2804,0.1982,0.2438,0.1789,0.1706,0.0762,0.0238,0.0268,0.0081,0.0129,0.0161,0.0063,0.0119,0.0194,0.0140,0.0332,0.0439,M\n",
      "\n",
      "0.1313,0.2339,0.3059,0.4264,0.4010,0.1791,0.1853,0.0055,0.1929,0.2231,0.2907,0.2259,0.3136,0.3302,0.3660,0.3956,0.4386,0.4670,0.5255,0.3735,0.2243,0.1973,0.4337,0.6532,0.5070,0.2796,0.4163,0.5950,0.5242,0.4178,0.3714,0.2375,0.0863,0.1437,0.2896,0.4577,0.3725,0.3372,0.3803,0.4181,0.3603,0.2711,0.1653,0.1951,0.2811,0.2246,0.1921,0.1500,0.0665,0.0193,0.0156,0.0362,0.0210,0.0154,0.0180,0.0013,0.0106,0.0127,0.0178,0.0231,M\n",
      "\n",
      "0.0201,0.0423,0.0554,0.0783,0.0620,0.0871,0.1201,0.2707,0.1206,0.0279,0.2251,0.2615,0.1770,0.3709,0.4533,0.5553,0.4616,0.3797,0.3450,0.2665,0.2395,0.1127,0.2556,0.5169,0.3779,0.4082,0.5353,0.5116,0.4544,0.4258,0.3869,0.3939,0.4661,0.3974,0.2194,0.1816,0.1023,0.2108,0.3253,0.3697,0.2912,0.3010,0.2563,0.1927,0.2062,0.1751,0.0841,0.1035,0.0641,0.0153,0.0081,0.0191,0.0182,0.0160,0.0290,0.0090,0.0242,0.0224,0.0190,0.0096,M\n",
      "\n",
      "0.0629,0.1065,0.1526,0.1229,0.1437,0.1190,0.0884,0.0907,0.2107,0.3597,0.5466,0.5205,0.5127,0.5395,0.6558,0.8705,0.9786,0.9335,0.7917,0.7383,0.6908,0.3850,0.0671,0.0502,0.2717,0.2839,0.2234,0.1911,0.0408,0.2531,0.1979,0.1891,0.2433,0.1956,0.2667,0.1340,0.1073,0.2023,0.1794,0.0227,0.1313,0.1775,0.1549,0.1626,0.0708,0.0129,0.0795,0.0762,0.0117,0.0061,0.0257,0.0089,0.0262,0.0108,0.0138,0.0187,0.0230,0.0057,0.0113,0.0131,M\n",
      "\n",
      "0.0335,0.0134,0.0696,0.1180,0.0348,0.1180,0.1948,0.1607,0.3036,0.4372,0.5533,0.5771,0.7022,0.7067,0.7367,0.7391,0.8622,0.9458,0.8782,0.7913,0.5760,0.3061,0.0563,0.0239,0.2554,0.4862,0.5027,0.4402,0.2847,0.1797,0.3560,0.3522,0.3321,0.3112,0.3638,0.0754,0.1834,0.1820,0.1815,0.1593,0.0576,0.0954,0.1086,0.0812,0.0784,0.0487,0.0439,0.0586,0.0370,0.0185,0.0302,0.0244,0.0232,0.0093,0.0159,0.0193,0.0032,0.0377,0.0126,0.0156,M\n",
      "\n",
      "0.0587,0.1210,0.1268,0.1498,0.1436,0.0561,0.0832,0.0672,0.1372,0.2352,0.3208,0.4257,0.5201,0.4914,0.5950,0.7221,0.9039,0.9111,0.8723,0.7686,0.7326,0.5222,0.3097,0.3172,0.2270,0.1640,0.1746,0.1835,0.2048,0.1674,0.2767,0.3104,0.3399,0.4441,0.5046,0.2814,0.1681,0.2633,0.3198,0.1933,0.0934,0.0443,0.0780,0.0722,0.0405,0.0553,0.1081,0.1139,0.0767,0.0265,0.0215,0.0331,0.0111,0.0088,0.0158,0.0122,0.0038,0.0101,0.0228,0.0124,M\n",
      "\n",
      "0.0162,0.0253,0.0262,0.0386,0.0645,0.0472,0.1056,0.1388,0.0598,0.1334,0.2969,0.4754,0.5677,0.5690,0.6421,0.7487,0.8999,1.0000,0.9690,0.9032,0.7685,0.6998,0.6644,0.5964,0.3711,0.0921,0.0481,0.0876,0.1040,0.1714,0.3264,0.4612,0.3939,0.5050,0.4833,0.3511,0.2319,0.4029,0.3676,0.1510,0.0745,0.1395,0.1552,0.0377,0.0636,0.0443,0.0264,0.0223,0.0187,0.0077,0.0137,0.0071,0.0082,0.0232,0.0198,0.0074,0.0035,0.0100,0.0048,0.0019,M\n",
      "\n",
      "0.0307,0.0523,0.0653,0.0521,0.0611,0.0577,0.0665,0.0664,0.1460,0.2792,0.3877,0.4992,0.4981,0.4972,0.5607,0.7339,0.8230,0.9173,0.9975,0.9911,0.8240,0.6498,0.5980,0.4862,0.3150,0.1543,0.0989,0.0284,0.1008,0.2636,0.2694,0.2930,0.2925,0.3998,0.3660,0.3172,0.4609,0.4374,0.1820,0.3376,0.6202,0.4448,0.1863,0.1420,0.0589,0.0576,0.0672,0.0269,0.0245,0.0190,0.0063,0.0321,0.0189,0.0137,0.0277,0.0152,0.0052,0.0121,0.0124,0.0055,M\n",
      "\n",
      "0.0116,0.0179,0.0449,0.1096,0.1913,0.0924,0.0761,0.1092,0.0757,0.1006,0.2500,0.3988,0.3809,0.4753,0.6165,0.6464,0.8024,0.9208,0.9832,0.9634,0.8646,0.8325,0.8276,0.8007,0.6102,0.4853,0.4355,0.4307,0.4399,0.3833,0.3032,0.3035,0.3197,0.2292,0.2131,0.2347,0.3201,0.4455,0.3655,0.2715,0.1747,0.1781,0.2199,0.1056,0.0573,0.0307,0.0237,0.0470,0.0102,0.0057,0.0031,0.0163,0.0099,0.0084,0.0270,0.0277,0.0097,0.0054,0.0148,0.0092,M\n",
      "\n",
      "0.0331,0.0423,0.0474,0.0818,0.0835,0.0756,0.0374,0.0961,0.0548,0.0193,0.0897,0.1734,0.1936,0.2803,0.3313,0.5020,0.6360,0.7096,0.8333,0.8730,0.8073,0.7507,0.7526,0.7298,0.6177,0.4946,0.4531,0.4099,0.4540,0.4124,0.3139,0.3194,0.3692,0.3776,0.4469,0.4777,0.4716,0.4664,0.3893,0.4255,0.4064,0.3712,0.3863,0.2802,0.1283,0.1117,0.1303,0.0787,0.0436,0.0224,0.0133,0.0078,0.0174,0.0176,0.0038,0.0129,0.0066,0.0044,0.0134,0.0092,M\n",
      "\n",
      "0.0428,0.0555,0.0708,0.0618,0.1215,0.1524,0.1543,0.0391,0.0610,0.0113,0.1255,0.2473,0.3011,0.3747,0.4520,0.5392,0.6588,0.7113,0.7602,0.8672,0.8416,0.7974,0.8385,0.9317,0.8555,0.6162,0.4139,0.3269,0.3108,0.2554,0.3367,0.4465,0.5000,0.5111,0.5194,0.4619,0.4234,0.4372,0.4277,0.4433,0.3700,0.3324,0.2564,0.2527,0.2137,0.1789,0.1010,0.0528,0.0453,0.0118,0.0009,0.0142,0.0179,0.0079,0.0060,0.0131,0.0089,0.0084,0.0113,0.0049,M\n",
      "\n",
      "0.0599,0.0474,0.0498,0.0387,0.1026,0.0773,0.0853,0.0447,0.1094,0.0351,0.1582,0.2023,0.2268,0.2829,0.3819,0.4665,0.6687,0.8647,0.9361,0.9367,0.9144,0.9162,0.9311,0.8604,0.7327,0.5763,0.4162,0.4113,0.4146,0.3149,0.2936,0.3169,0.3149,0.4132,0.3994,0.4195,0.4532,0.4419,0.4737,0.3431,0.3194,0.3370,0.2493,0.2650,0.1748,0.0932,0.0530,0.0081,0.0342,0.0137,0.0028,0.0013,0.0005,0.0227,0.0209,0.0081,0.0117,0.0114,0.0112,0.0100,M\n",
      "\n",
      "0.0264,0.0071,0.0342,0.0793,0.1043,0.0783,0.1417,0.1176,0.0453,0.0945,0.1132,0.0840,0.0717,0.1968,0.2633,0.4191,0.5050,0.6711,0.7922,0.8381,0.8759,0.9422,1.0000,0.9931,0.9575,0.8647,0.7215,0.5801,0.4964,0.4886,0.4079,0.2443,0.1768,0.2472,0.3518,0.3762,0.2909,0.2311,0.3168,0.3554,0.3741,0.4443,0.3261,0.1963,0.0864,0.1688,0.1991,0.1217,0.0628,0.0323,0.0253,0.0214,0.0262,0.0177,0.0037,0.0068,0.0121,0.0077,0.0078,0.0066,M\n",
      "\n",
      "0.0210,0.0121,0.0203,0.1036,0.1675,0.0418,0.0723,0.0828,0.0494,0.0686,0.1125,0.1741,0.2710,0.3087,0.3575,0.4998,0.6011,0.6470,0.8067,0.9008,0.8906,0.9338,1.0000,0.9102,0.8496,0.7867,0.7688,0.7718,0.6268,0.4301,0.2077,0.1198,0.1660,0.2618,0.3862,0.3958,0.3248,0.2302,0.3250,0.4022,0.4344,0.4008,0.3370,0.2518,0.2101,0.1181,0.1150,0.0550,0.0293,0.0183,0.0104,0.0117,0.0101,0.0061,0.0031,0.0099,0.0080,0.0107,0.0161,0.0133,M\n",
      "\n",
      "0.0530,0.0885,0.1997,0.2604,0.3225,0.2247,0.0617,0.2287,0.0950,0.0740,0.1610,0.2226,0.2703,0.3365,0.4266,0.4144,0.5655,0.6921,0.8547,0.9234,0.9171,1.0000,0.9532,0.9101,0.8337,0.7053,0.6534,0.4483,0.2460,0.2020,0.1446,0.0994,0.1510,0.2392,0.4434,0.5023,0.4441,0.4571,0.3927,0.2900,0.3408,0.4990,0.3632,0.1387,0.1800,0.1299,0.0523,0.0817,0.0469,0.0114,0.0299,0.0244,0.0199,0.0257,0.0082,0.0151,0.0171,0.0146,0.0134,0.0056,M\n",
      "\n",
      "0.0454,0.0472,0.0697,0.1021,0.1397,0.1493,0.1487,0.0771,0.1171,0.1675,0.2799,0.3323,0.4012,0.4296,0.5350,0.5411,0.6870,0.8045,0.9194,0.9169,1.0000,0.9972,0.9093,0.7918,0.6705,0.5324,0.3572,0.2484,0.3161,0.3775,0.3138,0.1713,0.2937,0.5234,0.5926,0.5437,0.4516,0.3379,0.3215,0.2178,0.1674,0.2634,0.2980,0.2037,0.1155,0.0919,0.0882,0.0228,0.0380,0.0142,0.0137,0.0120,0.0042,0.0238,0.0129,0.0084,0.0218,0.0321,0.0154,0.0053,M\n",
      "\n",
      "0.0283,0.0599,0.0656,0.0229,0.0839,0.1673,0.1154,0.1098,0.1370,0.1767,0.1995,0.2869,0.3275,0.3769,0.4169,0.5036,0.6180,0.8025,0.9333,0.9399,0.9275,0.9450,0.8328,0.7773,0.7007,0.6154,0.5810,0.4454,0.3707,0.2891,0.2185,0.1711,0.3578,0.3947,0.2867,0.2401,0.3619,0.3314,0.3763,0.4767,0.4059,0.3661,0.2320,0.1450,0.1017,0.1111,0.0655,0.0271,0.0244,0.0179,0.0109,0.0147,0.0170,0.0158,0.0046,0.0073,0.0054,0.0033,0.0045,0.0079,M\n",
      "\n",
      "0.0114,0.0222,0.0269,0.0384,0.1217,0.2062,0.1489,0.0929,0.1350,0.1799,0.2486,0.2973,0.3672,0.4394,0.5258,0.6755,0.7402,0.8284,0.9033,0.9584,1.0000,0.9982,0.8899,0.7493,0.6367,0.6744,0.7207,0.6821,0.5512,0.4789,0.3924,0.2533,0.1089,0.1390,0.2551,0.3301,0.2818,0.2142,0.2266,0.2142,0.2354,0.2871,0.2596,0.1925,0.1256,0.1003,0.0951,0.1210,0.0728,0.0174,0.0213,0.0269,0.0152,0.0257,0.0097,0.0041,0.0050,0.0145,0.0103,0.0025,M\n",
      "\n",
      "0.0414,0.0436,0.0447,0.0844,0.0419,0.1215,0.2002,0.1516,0.0818,0.1975,0.2309,0.3025,0.3938,0.5050,0.5872,0.6610,0.7417,0.8006,0.8456,0.7939,0.8804,0.8384,0.7852,0.8479,0.7434,0.6433,0.5514,0.3519,0.3168,0.3346,0.2056,0.1032,0.3168,0.4040,0.4282,0.4538,0.3704,0.3741,0.3839,0.3494,0.4380,0.4265,0.2854,0.2808,0.2395,0.0369,0.0805,0.0541,0.0177,0.0065,0.0222,0.0045,0.0136,0.0113,0.0053,0.0165,0.0141,0.0077,0.0246,0.0198,M\n",
      "\n",
      "0.0094,0.0333,0.0306,0.0376,0.1296,0.1795,0.1909,0.1692,0.1870,0.1725,0.2228,0.3106,0.4144,0.5157,0.5369,0.5107,0.6441,0.7326,0.8164,0.8856,0.9891,1.0000,0.8750,0.8631,0.9074,0.8674,0.7750,0.6600,0.5615,0.4016,0.2331,0.1164,0.1095,0.0431,0.0619,0.1956,0.2120,0.3242,0.4102,0.2939,0.1911,0.1702,0.1010,0.1512,0.1427,0.1097,0.1173,0.0972,0.0703,0.0281,0.0216,0.0153,0.0112,0.0241,0.0164,0.0055,0.0078,0.0055,0.0091,0.0067,M\n",
      "\n",
      "0.0228,0.0106,0.0130,0.0842,0.1117,0.1506,0.1776,0.0997,0.1428,0.2227,0.2621,0.3109,0.2859,0.3316,0.3755,0.4499,0.4765,0.6254,0.7304,0.8702,0.9349,0.9614,0.9126,0.9443,1.0000,0.9455,0.8815,0.7520,0.7068,0.5986,0.3857,0.2510,0.2162,0.0968,0.1323,0.1344,0.2250,0.3244,0.3939,0.3806,0.3258,0.3654,0.2983,0.1779,0.1535,0.1199,0.0959,0.0765,0.0649,0.0313,0.0185,0.0098,0.0178,0.0077,0.0074,0.0095,0.0055,0.0045,0.0063,0.0039,M\n",
      "\n",
      "0.0363,0.0478,0.0298,0.0210,0.1409,0.1916,0.1349,0.1613,0.1703,0.1444,0.1989,0.2154,0.2863,0.3570,0.3980,0.4359,0.5334,0.6304,0.6995,0.7435,0.8379,0.8641,0.9014,0.9432,0.9536,1.0000,0.9547,0.9745,0.8962,0.7196,0.5462,0.3156,0.2525,0.1969,0.2189,0.1533,0.0711,0.1498,0.1755,0.2276,0.1322,0.1056,0.1973,0.1692,0.1881,0.1177,0.0779,0.0495,0.0492,0.0194,0.0250,0.0115,0.0190,0.0055,0.0096,0.0050,0.0066,0.0114,0.0073,0.0033,M\n",
      "\n",
      "0.0261,0.0266,0.0223,0.0749,0.1364,0.1513,0.1316,0.1654,0.1864,0.2013,0.2890,0.3650,0.3510,0.3495,0.4325,0.5398,0.6237,0.6876,0.7329,0.8107,0.8396,0.8632,0.8747,0.9607,0.9716,0.9121,0.8576,0.8798,0.7720,0.5711,0.4264,0.2860,0.3114,0.2066,0.1165,0.0185,0.1302,0.2480,0.1637,0.1103,0.2144,0.2033,0.1887,0.1370,0.1376,0.0307,0.0373,0.0606,0.0399,0.0169,0.0135,0.0222,0.0175,0.0127,0.0022,0.0124,0.0054,0.0021,0.0028,0.0023,M\n",
      "\n",
      "0.0346,0.0509,0.0079,0.0243,0.0432,0.0735,0.0938,0.1134,0.1228,0.1508,0.1809,0.2390,0.2947,0.2866,0.4010,0.5325,0.5486,0.5823,0.6041,0.6749,0.7084,0.7890,0.9284,0.9781,0.9738,1.0000,0.9702,0.9956,0.8235,0.6020,0.5342,0.4867,0.3526,0.1566,0.0946,0.1613,0.2824,0.3390,0.3019,0.2945,0.2978,0.2676,0.2055,0.2069,0.1625,0.1216,0.1013,0.0744,0.0386,0.0050,0.0146,0.0040,0.0122,0.0107,0.0112,0.0102,0.0052,0.0024,0.0079,0.0031,M\n",
      "\n",
      "0.0162,0.0041,0.0239,0.0441,0.0630,0.0921,0.1368,0.1078,0.1552,0.1779,0.2164,0.2568,0.3089,0.3829,0.4393,0.5335,0.5996,0.6728,0.7309,0.8092,0.8941,0.9668,1.0000,0.9893,0.9376,0.8991,0.9184,0.9128,0.7811,0.6018,0.3765,0.3300,0.2280,0.0212,0.1117,0.1788,0.2373,0.2843,0.2241,0.2715,0.3363,0.2546,0.1867,0.2160,0.1278,0.0768,0.1070,0.0946,0.0636,0.0227,0.0128,0.0173,0.0135,0.0114,0.0062,0.0157,0.0088,0.0036,0.0053,0.0030,M\n",
      "\n",
      "0.0249,0.0119,0.0277,0.0760,0.1218,0.1538,0.1192,0.1229,0.2119,0.2531,0.2855,0.2961,0.3341,0.4287,0.5205,0.6087,0.7236,0.7577,0.7726,0.8098,0.8995,0.9247,0.9365,0.9853,0.9776,1.0000,0.9896,0.9076,0.7306,0.5758,0.4469,0.3719,0.2079,0.0955,0.0488,0.1406,0.2554,0.2054,0.1614,0.2232,0.1773,0.2293,0.2521,0.1464,0.0673,0.0965,0.1492,0.1128,0.0463,0.0193,0.0140,0.0027,0.0068,0.0150,0.0012,0.0133,0.0048,0.0244,0.0077,0.0074,M\n",
      "\n",
      "0.0270,0.0163,0.0341,0.0247,0.0822,0.1256,0.1323,0.1584,0.2017,0.2122,0.2210,0.2399,0.2964,0.4061,0.5095,0.5512,0.6613,0.6804,0.6520,0.6788,0.7811,0.8369,0.8969,0.9856,1.0000,0.9395,0.8917,0.8105,0.6828,0.5572,0.4301,0.3339,0.2035,0.0798,0.0809,0.1525,0.2626,0.2456,0.1980,0.2412,0.2409,0.1901,0.2077,0.1767,0.1119,0.0779,0.1344,0.0960,0.0598,0.0330,0.0197,0.0189,0.0204,0.0085,0.0043,0.0092,0.0138,0.0094,0.0105,0.0093,M\n",
      "\n",
      "0.0388,0.0324,0.0688,0.0898,0.1267,0.1515,0.2134,0.2613,0.2832,0.2718,0.3645,0.3934,0.3843,0.4677,0.5364,0.4823,0.4835,0.5862,0.7579,0.6997,0.6918,0.8633,0.9107,0.9346,0.7884,0.8585,0.9261,0.7080,0.5779,0.5215,0.4505,0.3129,0.1448,0.1046,0.1820,0.1519,0.1017,0.1438,0.1986,0.2039,0.2778,0.2879,0.1331,0.1140,0.1310,0.1433,0.0624,0.0100,0.0098,0.0131,0.0152,0.0255,0.0071,0.0263,0.0079,0.0111,0.0107,0.0068,0.0097,0.0067,M\n",
      "\n",
      "0.0228,0.0853,0.1000,0.0428,0.1117,0.1651,0.1597,0.2116,0.3295,0.3517,0.3330,0.3643,0.4020,0.4731,0.5196,0.6573,0.8426,0.8476,0.8344,0.8453,0.7999,0.8537,0.9642,1.0000,0.9357,0.9409,0.9070,0.7104,0.6320,0.5667,0.3501,0.2447,0.1698,0.3290,0.3674,0.2331,0.2413,0.2556,0.1892,0.1940,0.3074,0.2785,0.0308,0.1238,0.1854,0.1753,0.1079,0.0728,0.0242,0.0191,0.0159,0.0172,0.0191,0.0260,0.0140,0.0125,0.0116,0.0093,0.0012,0.0036,M\n",
      "\n",
      "0.0715,0.0849,0.0587,0.0218,0.0862,0.1801,0.1916,0.1896,0.2960,0.4186,0.4867,0.5249,0.5959,0.6855,0.8573,0.9718,0.8693,0.8711,0.8954,0.9922,0.8980,0.8158,0.8373,0.7541,0.5893,0.5488,0.5643,0.5406,0.4783,0.4439,0.3698,0.2574,0.1478,0.1743,0.1229,0.1588,0.1803,0.1436,0.1667,0.2630,0.2234,0.1239,0.0869,0.2092,0.1499,0.0676,0.0899,0.0927,0.0658,0.0086,0.0216,0.0153,0.0121,0.0096,0.0196,0.0042,0.0066,0.0099,0.0083,0.0124,M\n",
      "\n",
      "0.0209,0.0261,0.0120,0.0768,0.1064,0.1680,0.3016,0.3460,0.3314,0.4125,0.3943,0.1334,0.4622,0.9970,0.9137,0.8292,0.6994,0.7825,0.8789,0.8501,0.8920,0.9473,1.0000,0.8975,0.7806,0.8321,0.6502,0.4548,0.4732,0.3391,0.2747,0.0978,0.0477,0.1403,0.1834,0.2148,0.1271,0.1912,0.3391,0.3444,0.2369,0.1195,0.2665,0.2587,0.1393,0.1083,0.1383,0.1321,0.1069,0.0325,0.0316,0.0057,0.0159,0.0085,0.0372,0.0101,0.0127,0.0288,0.0129,0.0023,M\n",
      "\n",
      "0.0374,0.0586,0.0628,0.0534,0.0255,0.1422,0.2072,0.2734,0.3070,0.2597,0.3483,0.3999,0.4574,0.5950,0.7924,0.8272,0.8087,0.8977,0.9828,0.8982,0.8890,0.9367,0.9122,0.7936,0.6718,0.6318,0.4865,0.3388,0.4832,0.3822,0.3075,0.1267,0.0743,0.1510,0.1906,0.1817,0.1709,0.0946,0.2829,0.3006,0.1602,0.1483,0.2875,0.2047,0.1064,0.1395,0.1065,0.0527,0.0395,0.0183,0.0353,0.0118,0.0063,0.0237,0.0032,0.0087,0.0124,0.0113,0.0098,0.0126,M\n",
      "\n",
      "0.1371,0.1226,0.1385,0.1484,0.1776,0.1428,0.1773,0.2161,0.1630,0.2067,0.4257,0.5484,0.7131,0.7003,0.6777,0.7939,0.9382,0.8925,0.9146,0.7832,0.7960,0.7983,0.7716,0.6615,0.4860,0.5572,0.4697,0.5640,0.4517,0.3369,0.2684,0.2339,0.3052,0.3016,0.2753,0.1041,0.1757,0.3156,0.3603,0.2736,0.1301,0.2458,0.3404,0.1753,0.0679,0.1062,0.0643,0.0532,0.0531,0.0272,0.0171,0.0118,0.0129,0.0344,0.0065,0.0067,0.0022,0.0079,0.0146,0.0051,M\n",
      "\n",
      "0.0443,0.0446,0.0235,0.1008,0.2252,0.2611,0.2061,0.1668,0.1801,0.3083,0.3794,0.5364,0.6173,0.7842,0.8392,0.9016,1.0000,0.8911,0.8753,0.7886,0.7156,0.7581,0.6372,0.3210,0.2076,0.2279,0.3309,0.2847,0.1949,0.1671,0.1025,0.1362,0.2212,0.1124,0.1677,0.1039,0.2562,0.2624,0.2236,0.1180,0.1103,0.2831,0.2385,0.0255,0.1967,0.1483,0.0434,0.0627,0.0513,0.0473,0.0248,0.0274,0.0205,0.0141,0.0185,0.0055,0.0045,0.0115,0.0152,0.0100,M\n",
      "\n",
      "0.1150,0.1163,0.0866,0.0358,0.0232,0.1267,0.2417,0.2661,0.4346,0.5378,0.3816,0.0991,0.0616,0.1795,0.3907,0.3602,0.3041,0.2428,0.4060,0.8395,0.9777,0.4680,0.0610,0.2143,0.1348,0.2854,0.1617,0.2649,0.4565,0.6502,0.2848,0.3296,0.5370,0.6627,0.8626,0.8547,0.7848,0.9016,0.8827,0.6086,0.2810,0.0906,0.1177,0.2694,0.5214,0.4232,0.2340,0.1928,0.1092,0.0507,0.0228,0.0099,0.0065,0.0085,0.0166,0.0110,0.0190,0.0141,0.0068,0.0086,M\n",
      "\n",
      "0.0968,0.0821,0.0629,0.0608,0.0617,0.1207,0.0944,0.4223,0.5744,0.5025,0.3488,0.1700,0.2076,0.3087,0.4224,0.5312,0.2436,0.1884,0.1908,0.8321,1.0000,0.4076,0.0960,0.1928,0.2419,0.3790,0.2893,0.3451,0.3777,0.5213,0.2316,0.3335,0.4781,0.6116,0.6705,0.7375,0.7356,0.7792,0.6788,0.5259,0.2762,0.1545,0.2019,0.2231,0.4221,0.3067,0.1329,0.1349,0.1057,0.0499,0.0206,0.0073,0.0081,0.0303,0.0190,0.0212,0.0126,0.0201,0.0210,0.0041,M\n",
      "\n",
      "0.0790,0.0707,0.0352,0.1660,0.1330,0.0226,0.0771,0.2678,0.5664,0.6609,0.5002,0.2583,0.1650,0.4347,0.4515,0.4579,0.3366,0.4000,0.5325,0.9010,0.9939,0.3689,0.1012,0.0248,0.2318,0.3981,0.2259,0.5247,0.6898,0.8316,0.4326,0.3741,0.5756,0.8043,0.7963,0.7174,0.7056,0.8148,0.7601,0.6034,0.4554,0.4729,0.4478,0.3722,0.4693,0.3839,0.0768,0.1467,0.0777,0.0469,0.0193,0.0298,0.0390,0.0294,0.0175,0.0249,0.0141,0.0073,0.0025,0.0101,M\n",
      "\n",
      "0.1083,0.1070,0.0257,0.0837,0.0748,0.1125,0.3322,0.4590,0.5526,0.5966,0.5304,0.2251,0.2402,0.2689,0.6646,0.6632,0.1674,0.0837,0.4331,0.8718,0.7992,0.3712,0.1703,0.1611,0.2086,0.2847,0.2211,0.6134,0.5807,0.6925,0.3825,0.4303,0.7791,0.8703,1.0000,0.9212,0.9386,0.9303,0.7314,0.4791,0.2087,0.2016,0.1669,0.2872,0.4374,0.3097,0.1578,0.0553,0.0334,0.0209,0.0172,0.0180,0.0110,0.0234,0.0276,0.0032,0.0084,0.0122,0.0082,0.0143,M\n",
      "\n",
      "0.0094,0.0611,0.1136,0.1203,0.0403,0.1227,0.2495,0.4566,0.6587,0.5079,0.3350,0.0834,0.3004,0.3957,0.3769,0.3828,0.1247,0.1363,0.2678,0.9188,0.9779,0.3236,0.1944,0.1874,0.0885,0.3443,0.2953,0.5908,0.4564,0.7334,0.1969,0.2790,0.6212,0.8681,0.8621,0.9380,0.8327,0.9480,0.6721,0.4436,0.5163,0.3809,0.1557,0.1449,0.2662,0.1806,0.1699,0.2559,0.1129,0.0201,0.0480,0.0234,0.0175,0.0352,0.0158,0.0326,0.0201,0.0168,0.0245,0.0154,M\n",
      "\n",
      "0.1088,0.1278,0.0926,0.1234,0.1276,0.1731,0.1948,0.4262,0.6828,0.5761,0.4733,0.2362,0.1023,0.2904,0.4713,0.4659,0.1415,0.0849,0.3257,0.9007,0.9312,0.4856,0.1346,0.1604,0.2737,0.5609,0.3654,0.6139,0.5470,0.8474,0.5638,0.5443,0.5086,0.6253,0.8497,0.8406,0.8420,0.9136,0.7713,0.4882,0.3724,0.4469,0.4586,0.4491,0.5616,0.4305,0.0945,0.0794,0.0274,0.0154,0.0140,0.0455,0.0213,0.0082,0.0124,0.0167,0.0103,0.0205,0.0178,0.0187,M\n",
      "\n",
      "0.0430,0.0902,0.0833,0.0813,0.0165,0.0277,0.0569,0.2057,0.3887,0.7106,0.7342,0.5033,0.3000,0.1951,0.2767,0.3737,0.2507,0.2507,0.3292,0.4871,0.6527,0.8454,0.9739,1.0000,0.6665,0.5323,0.4024,0.3444,0.4239,0.4182,0.4393,0.1162,0.4336,0.6553,0.6172,0.4373,0.4118,0.3641,0.4572,0.4367,0.2964,0.4312,0.4155,0.1824,0.1487,0.0138,0.1164,0.2052,0.1069,0.0199,0.0208,0.0176,0.0197,0.0210,0.0141,0.0049,0.0027,0.0162,0.0059,0.0021,M\n",
      "\n",
      "0.0731,0.1249,0.1665,0.1496,0.1443,0.2770,0.2555,0.1712,0.0466,0.1114,0.1739,0.3160,0.3249,0.2164,0.2031,0.2580,0.1796,0.2422,0.3609,0.1810,0.2604,0.6572,0.9734,0.9757,0.8079,0.6521,0.4915,0.5363,0.7649,0.5250,0.5101,0.4219,0.4160,0.1906,0.0223,0.4219,0.5496,0.2483,0.2034,0.2729,0.2837,0.4463,0.3178,0.0807,0.1192,0.2134,0.3241,0.2945,0.1474,0.0211,0.0361,0.0444,0.0230,0.0290,0.0141,0.0161,0.0177,0.0194,0.0207,0.0057,M\n",
      "\n",
      "0.0164,0.0627,0.0738,0.0608,0.0233,0.1048,0.1338,0.0644,0.1522,0.0780,0.1791,0.2681,0.1788,0.1039,0.1980,0.3234,0.3748,0.2586,0.3680,0.3508,0.5606,0.5231,0.5469,0.6954,0.6352,0.6757,0.8499,0.8025,0.6563,0.8591,0.6655,0.5369,0.3118,0.3763,0.2801,0.0875,0.3319,0.4237,0.1801,0.3743,0.4627,0.1614,0.2494,0.3202,0.2265,0.1146,0.0476,0.0943,0.0824,0.0171,0.0244,0.0258,0.0143,0.0226,0.0187,0.0185,0.0110,0.0094,0.0078,0.0112,M\n",
      "\n",
      "0.0412,0.1135,0.0518,0.0232,0.0646,0.1124,0.1787,0.2407,0.2682,0.2058,0.1546,0.2671,0.3141,0.2904,0.3531,0.5079,0.4639,0.1859,0.4474,0.4079,0.5400,0.4786,0.4332,0.6113,0.5091,0.4606,0.7243,0.8987,0.8826,0.9201,0.8005,0.6033,0.2120,0.2866,0.4033,0.2803,0.3087,0.3550,0.2545,0.1432,0.5869,0.6431,0.5826,0.4286,0.4894,0.5777,0.4315,0.2640,0.1794,0.0772,0.0798,0.0376,0.0143,0.0272,0.0127,0.0166,0.0095,0.0225,0.0098,0.0085,M\n",
      "\n",
      "0.0707,0.1252,0.1447,0.1644,0.1693,0.0844,0.0715,0.0947,0.1583,0.1247,0.2340,0.1764,0.2284,0.3115,0.4725,0.5543,0.5386,0.3746,0.4583,0.5961,0.7464,0.7644,0.5711,0.6257,0.6695,0.7131,0.7567,0.8077,0.8477,0.9289,0.9513,0.7995,0.4362,0.4048,0.4952,0.1712,0.3652,0.3763,0.2841,0.0427,0.5331,0.6952,0.4288,0.3063,0.5835,0.5692,0.2630,0.1196,0.0983,0.0374,0.0291,0.0156,0.0197,0.0135,0.0127,0.0138,0.0133,0.0131,0.0154,0.0218,M\n",
      "\n",
      "0.0526,0.0563,0.1219,0.1206,0.0246,0.1022,0.0539,0.0439,0.2291,0.1632,0.2544,0.2807,0.3011,0.3361,0.3024,0.2285,0.2910,0.1316,0.1151,0.3404,0.5562,0.6379,0.6553,0.7384,0.6534,0.5423,0.6877,0.7325,0.7726,0.8229,0.8787,0.9108,0.6705,0.6092,0.7505,0.4775,0.1666,0.3749,0.3776,0.2106,0.5886,0.5628,0.2577,0.5245,0.6149,0.5123,0.3385,0.1499,0.0546,0.0270,0.0380,0.0339,0.0149,0.0335,0.0376,0.0174,0.0132,0.0103,0.0364,0.0208,M\n",
      "\n",
      "0.0516,0.0944,0.0622,0.0415,0.0995,0.2431,0.1777,0.2018,0.2611,0.1294,0.2646,0.2778,0.4432,0.3672,0.2035,0.2764,0.3252,0.1536,0.2784,0.3508,0.5187,0.7052,0.7143,0.6814,0.5100,0.5308,0.6131,0.8388,0.9031,0.8607,0.9656,0.9168,0.7132,0.6898,0.7310,0.4134,0.1580,0.1819,0.1381,0.2960,0.6935,0.8246,0.5351,0.4403,0.6448,0.6214,0.3016,0.1379,0.0364,0.0355,0.0456,0.0432,0.0274,0.0152,0.0120,0.0129,0.0020,0.0109,0.0074,0.0078,M\n",
      "\n",
      "0.0299,0.0688,0.0992,0.1021,0.0800,0.0629,0.0130,0.0813,0.1761,0.0998,0.0523,0.0904,0.2655,0.3099,0.3520,0.3892,0.3962,0.2449,0.2355,0.3045,0.3112,0.4698,0.5534,0.4532,0.4464,0.4670,0.4621,0.6988,0.7626,0.7025,0.7382,0.7446,0.7927,0.5227,0.3967,0.3042,0.1309,0.2408,0.1780,0.1598,0.5657,0.6443,0.4241,0.4567,0.5760,0.5293,0.3287,0.1283,0.0698,0.0334,0.0342,0.0459,0.0277,0.0172,0.0087,0.0046,0.0203,0.0130,0.0115,0.0015,M\n",
      "\n",
      "0.0721,0.1574,0.1112,0.1085,0.0666,0.1800,0.1108,0.2794,0.1408,0.0795,0.2534,0.3920,0.3375,0.1610,0.1889,0.3308,0.2282,0.2177,0.1853,0.5167,0.5342,0.6298,0.8437,0.6756,0.5825,0.6141,0.8809,0.8375,0.3869,0.5051,0.5455,0.4241,0.1534,0.4950,0.6983,0.7109,0.5647,0.4870,0.5515,0.4433,0.5250,0.6075,0.5251,0.1359,0.4268,0.4442,0.2193,0.0900,0.1200,0.0628,0.0234,0.0309,0.0127,0.0082,0.0281,0.0117,0.0092,0.0147,0.0157,0.0129,M\n",
      "\n",
      "0.1021,0.0830,0.0577,0.0627,0.0635,0.1328,0.0988,0.1787,0.1199,0.1369,0.2509,0.2631,0.2796,0.2977,0.3823,0.3129,0.3956,0.2093,0.3218,0.3345,0.3184,0.2887,0.3610,0.2566,0.4106,0.4591,0.4722,0.7278,0.7591,0.6579,0.7514,0.6666,0.4903,0.5962,0.6552,0.4014,0.1188,0.3245,0.3107,0.1354,0.5109,0.7988,0.7517,0.5508,0.5858,0.7292,0.5522,0.3339,0.1608,0.0475,0.1004,0.0709,0.0317,0.0309,0.0252,0.0087,0.0177,0.0214,0.0227,0.0106,M\n",
      "\n",
      "0.0654,0.0649,0.0737,0.1132,0.2482,0.1257,0.1797,0.0989,0.2460,0.3422,0.2128,0.1377,0.4032,0.5684,0.2398,0.4331,0.5954,0.5772,0.8176,0.8835,0.5248,0.6373,0.8375,0.6699,0.7756,0.8750,0.8300,0.6896,0.3372,0.6405,0.7138,0.8202,0.6657,0.5254,0.2960,0.0704,0.0970,0.3941,0.6028,0.3521,0.3924,0.4808,0.4602,0.4164,0.5438,0.5649,0.3195,0.2484,0.1299,0.0825,0.0243,0.0210,0.0361,0.0239,0.0447,0.0394,0.0355,0.0440,0.0243,0.0098,M\n",
      "\n",
      "0.0712,0.0901,0.1276,0.1497,0.1284,0.1165,0.1285,0.1684,0.1830,0.2127,0.2891,0.3985,0.4576,0.5821,0.5027,0.1930,0.2579,0.3177,0.2745,0.6186,0.8958,0.7442,0.5188,0.2811,0.1773,0.6607,0.7576,0.5122,0.4701,0.5479,0.4347,0.1276,0.0846,0.0927,0.0313,0.0998,0.1781,0.1586,0.3001,0.2208,0.1455,0.2895,0.3203,0.1414,0.0629,0.0734,0.0805,0.0608,0.0565,0.0286,0.0154,0.0154,0.0156,0.0054,0.0030,0.0048,0.0087,0.0101,0.0095,0.0068,M\n",
      "\n",
      "0.0207,0.0535,0.0334,0.0818,0.0740,0.0324,0.0918,0.1070,0.1553,0.1234,0.1796,0.1787,0.1247,0.2577,0.3370,0.3990,0.1647,0.2266,0.3219,0.5356,0.8159,1.0000,0.8701,0.6889,0.6299,0.5738,0.5707,0.5976,0.4301,0.2058,0.1000,0.2247,0.2308,0.3977,0.3317,0.1726,0.1429,0.2168,0.1967,0.2140,0.3674,0.2023,0.0778,0.0925,0.2388,0.3400,0.2594,0.1102,0.0911,0.0462,0.0171,0.0033,0.0050,0.0190,0.0103,0.0121,0.0042,0.0090,0.0070,0.0099,M\n",
      "\n",
      "0.0209,0.0278,0.0115,0.0445,0.0427,0.0766,0.1458,0.1430,0.1894,0.1853,0.1748,0.1556,0.1476,0.1378,0.2584,0.3827,0.4784,0.5360,0.6192,0.7912,0.9264,1.0000,0.9080,0.7435,0.5557,0.3172,0.1295,0.0598,0.2722,0.3616,0.3293,0.4855,0.3936,0.1845,0.0342,0.2489,0.3837,0.3514,0.2654,0.1760,0.1599,0.0866,0.0590,0.0813,0.0492,0.0417,0.0495,0.0367,0.0115,0.0118,0.0133,0.0096,0.0014,0.0049,0.0039,0.0029,0.0078,0.0047,0.0021,0.0011,M\n",
      "\n",
      "0.0231,0.0315,0.0170,0.0226,0.0410,0.0116,0.0223,0.0805,0.2365,0.2461,0.2245,0.1520,0.1732,0.3099,0.4380,0.5595,0.6820,0.6164,0.6803,0.8435,0.9921,1.0000,0.7983,0.5426,0.3952,0.5179,0.5650,0.3042,0.1881,0.3960,0.2286,0.3544,0.4187,0.2398,0.1847,0.3760,0.4331,0.3626,0.2519,0.1870,0.1046,0.2339,0.1991,0.1100,0.0684,0.0303,0.0674,0.0785,0.0455,0.0246,0.0151,0.0125,0.0036,0.0123,0.0043,0.0114,0.0052,0.0091,0.0008,0.0092,M\n",
      "\n",
      "0.0131,0.0201,0.0045,0.0217,0.0230,0.0481,0.0742,0.0333,0.1369,0.2079,0.2295,0.1990,0.1184,0.1891,0.2949,0.5343,0.6850,0.7923,0.8220,0.7290,0.7352,0.7918,0.8057,0.4898,0.1934,0.2924,0.6255,0.8546,0.8966,0.7821,0.5168,0.4840,0.4038,0.3411,0.2849,0.2353,0.2699,0.4442,0.4323,0.3314,0.1195,0.1669,0.3702,0.3072,0.0945,0.1545,0.1394,0.0772,0.0615,0.0230,0.0111,0.0168,0.0086,0.0045,0.0062,0.0065,0.0030,0.0066,0.0029,0.0053,M\n",
      "\n",
      "0.0233,0.0394,0.0416,0.0547,0.0993,0.1515,0.1674,0.1513,0.1723,0.2078,0.1239,0.0236,0.1771,0.3115,0.4990,0.6707,0.7655,0.8485,0.9805,1.0000,1.0000,0.9992,0.9067,0.6803,0.5103,0.4716,0.4980,0.6196,0.7171,0.6316,0.3554,0.2897,0.4316,0.3791,0.2421,0.0944,0.0351,0.0844,0.0436,0.1130,0.2045,0.1937,0.0834,0.1502,0.1675,0.1058,0.1111,0.0849,0.0596,0.0201,0.0071,0.0104,0.0062,0.0026,0.0025,0.0061,0.0038,0.0101,0.0078,0.0006,M\n",
      "\n",
      "0.0117,0.0069,0.0279,0.0583,0.0915,0.1267,0.1577,0.1927,0.2361,0.2169,0.1180,0.0754,0.2782,0.3758,0.5093,0.6592,0.7071,0.7532,0.8357,0.8593,0.9615,0.9838,0.8705,0.6403,0.5067,0.5395,0.6934,0.8487,0.8213,0.5962,0.2950,0.2758,0.2885,0.1893,0.1446,0.0955,0.0888,0.0836,0.0894,0.1547,0.2318,0.2225,0.1035,0.1721,0.2017,0.1787,0.1112,0.0398,0.0305,0.0084,0.0039,0.0053,0.0029,0.0020,0.0013,0.0029,0.0020,0.0062,0.0026,0.0052,M\n",
      "\n",
      "0.0211,0.0128,0.0015,0.0450,0.0711,0.1563,0.1518,0.1206,0.1666,0.1345,0.0785,0.0367,0.1227,0.2614,0.4280,0.6122,0.7435,0.8130,0.9006,0.9603,0.9162,0.9140,0.7851,0.5134,0.3439,0.3290,0.2571,0.3685,0.5765,0.6190,0.4613,0.3615,0.4434,0.3864,0.3093,0.2138,0.1112,0.1386,0.1523,0.0996,0.1644,0.1902,0.1313,0.1776,0.2000,0.0765,0.0727,0.0749,0.0449,0.0134,0.0174,0.0117,0.0023,0.0047,0.0049,0.0031,0.0024,0.0039,0.0051,0.0015,M\n",
      "\n",
      "0.0047,0.0059,0.0080,0.0554,0.0883,0.1278,0.1674,0.1373,0.2922,0.3469,0.3265,0.3263,0.2301,0.1253,0.2102,0.2401,0.1928,0.1673,0.1228,0.0902,0.1557,0.3291,0.5268,0.6740,0.7906,0.8938,0.9395,0.9493,0.9040,0.9151,0.8828,0.8086,0.7180,0.6720,0.6447,0.6879,0.6241,0.4936,0.4144,0.4240,0.4546,0.4392,0.4323,0.4921,0.4710,0.3196,0.2241,0.1806,0.0990,0.0251,0.0129,0.0095,0.0126,0.0069,0.0039,0.0068,0.0060,0.0045,0.0002,0.0029,M\n",
      "\n",
      "0.0201,0.0178,0.0274,0.0232,0.0724,0.0833,0.1232,0.1298,0.2085,0.2720,0.2188,0.3037,0.2959,0.2059,0.0906,0.1610,0.1800,0.2180,0.2026,0.1506,0.0521,0.2143,0.4333,0.5943,0.6926,0.7576,0.8787,0.9060,0.8528,0.9087,0.9657,0.9306,0.7774,0.6643,0.6604,0.6884,0.6938,0.5932,0.5774,0.6223,0.5841,0.4527,0.4911,0.5762,0.5013,0.4042,0.3123,0.2232,0.1085,0.0414,0.0253,0.0131,0.0049,0.0104,0.0102,0.0092,0.0083,0.0020,0.0048,0.0036,M\n",
      "\n",
      "0.0107,0.0453,0.0289,0.0713,0.1075,0.1019,0.1606,0.2119,0.3061,0.2936,0.3104,0.3431,0.2456,0.1887,0.1184,0.2080,0.2736,0.3274,0.2344,0.1260,0.0576,0.1241,0.3239,0.4357,0.5734,0.7825,0.9252,0.9349,0.9348,1.0000,0.9308,0.8478,0.7605,0.7040,0.7539,0.7990,0.7673,0.5955,0.4731,0.4840,0.4340,0.3954,0.4837,0.5379,0.4485,0.2674,0.1541,0.1359,0.0941,0.0261,0.0079,0.0164,0.0120,0.0113,0.0021,0.0097,0.0072,0.0060,0.0017,0.0036,M\n",
      "\n",
      "0.0235,0.0220,0.0167,0.0516,0.0746,0.1121,0.1258,0.1717,0.3074,0.3199,0.2946,0.2484,0.2510,0.1806,0.1413,0.3019,0.3635,0.3887,0.2980,0.2219,0.1624,0.1343,0.2046,0.3791,0.5771,0.7545,0.8406,0.8547,0.9036,1.0000,0.9646,0.7912,0.6412,0.5986,0.6835,0.7771,0.8084,0.7426,0.6295,0.5708,0.4433,0.3361,0.3795,0.4950,0.4373,0.2404,0.1128,0.1654,0.0933,0.0225,0.0214,0.0221,0.0152,0.0083,0.0058,0.0023,0.0057,0.0052,0.0027,0.0021,M\n",
      "\n",
      "0.0258,0.0433,0.0547,0.0681,0.0784,0.1250,0.1296,0.1729,0.2794,0.2954,0.2506,0.2601,0.2249,0.2115,0.1270,0.1193,0.1794,0.2185,0.1646,0.0740,0.0625,0.2381,0.4824,0.6372,0.7531,0.8959,0.9941,0.9957,0.9328,0.9344,0.8854,0.7690,0.6865,0.6390,0.6378,0.6629,0.5983,0.4565,0.3129,0.4158,0.4325,0.4031,0.4201,0.4557,0.3955,0.2966,0.2095,0.1558,0.0884,0.0265,0.0121,0.0091,0.0062,0.0019,0.0045,0.0079,0.0031,0.0063,0.0048,0.0050,M\n",
      "\n",
      "0.0305,0.0363,0.0214,0.0227,0.0456,0.0665,0.0939,0.0972,0.2535,0.3127,0.2192,0.2621,0.2419,0.2179,0.1159,0.1237,0.0886,0.1755,0.1758,0.1540,0.0512,0.1805,0.4039,0.5697,0.6577,0.7474,0.8543,0.9085,0.8668,0.8892,0.9065,0.8522,0.7204,0.6200,0.6253,0.6848,0.7337,0.6281,0.5725,0.6119,0.5597,0.4965,0.5027,0.5772,0.5907,0.4803,0.3877,0.2779,0.1427,0.0424,0.0271,0.0200,0.0070,0.0070,0.0086,0.0089,0.0074,0.0042,0.0055,0.0021,M\n",
      "\n",
      "0.0217,0.0152,0.0346,0.0346,0.0484,0.0526,0.0773,0.0862,0.1451,0.2110,0.2343,0.2087,0.1645,0.1689,0.1650,0.1967,0.2934,0.3709,0.4309,0.4161,0.5116,0.6501,0.7717,0.8491,0.9104,0.8912,0.8189,0.6779,0.5368,0.5207,0.5651,0.5749,0.5250,0.4255,0.3330,0.2331,0.1451,0.1648,0.2694,0.3730,0.4467,0.4133,0.3743,0.3021,0.2069,0.1790,0.1689,0.1341,0.0769,0.0222,0.0205,0.0123,0.0067,0.0011,0.0026,0.0049,0.0029,0.0022,0.0022,0.0032,M\n",
      "\n",
      "0.0072,0.0027,0.0089,0.0061,0.0420,0.0865,0.1182,0.0999,0.1976,0.2318,0.2472,0.2880,0.2126,0.0708,0.1194,0.2808,0.4221,0.5279,0.5857,0.6153,0.6753,0.7873,0.8974,0.9828,1.0000,0.8460,0.6055,0.3036,0.0144,0.2526,0.4335,0.4918,0.5409,0.5961,0.5248,0.3777,0.2369,0.1720,0.1878,0.3250,0.2575,0.2423,0.2706,0.2323,0.1724,0.1457,0.1175,0.0868,0.0392,0.0131,0.0092,0.0078,0.0071,0.0081,0.0034,0.0064,0.0037,0.0036,0.0012,0.0037,M\n",
      "\n",
      "0.0163,0.0198,0.0202,0.0386,0.0752,0.1444,0.1487,0.1484,0.2442,0.2822,0.3691,0.3750,0.3927,0.3308,0.1085,0.1139,0.3446,0.5441,0.6470,0.7276,0.7894,0.8264,0.8697,0.7836,0.7140,0.5698,0.2908,0.4636,0.6409,0.7405,0.8069,0.8420,1.0000,0.9536,0.6755,0.3905,0.1249,0.3629,0.6356,0.8116,0.7664,0.5417,0.2614,0.1723,0.2814,0.2764,0.1985,0.1502,0.1219,0.0493,0.0027,0.0077,0.0026,0.0031,0.0083,0.0020,0.0084,0.0108,0.0083,0.0033,M\n",
      "\n",
      "0.0221,0.0065,0.0164,0.0487,0.0519,0.0849,0.0812,0.1833,0.2228,0.1810,0.2549,0.2984,0.2624,0.1893,0.0668,0.2666,0.4274,0.6291,0.7782,0.7686,0.8099,0.8493,0.9440,0.9450,0.9655,0.8045,0.4969,0.3960,0.3856,0.5574,0.7309,0.8549,0.9425,0.8726,0.6673,0.4694,0.1546,0.1748,0.3607,0.5208,0.5177,0.3702,0.2240,0.0816,0.0395,0.0785,0.1052,0.1034,0.0764,0.0216,0.0167,0.0089,0.0051,0.0015,0.0075,0.0058,0.0016,0.0070,0.0074,0.0038,M\n",
      "\n",
      "0.0411,0.0277,0.0604,0.0525,0.0489,0.0385,0.0611,0.1117,0.1237,0.2300,0.1370,0.1335,0.2137,0.1526,0.0775,0.1196,0.0903,0.0689,0.2071,0.2975,0.2836,0.3353,0.3622,0.3202,0.3452,0.3562,0.3892,0.6622,0.9254,1.0000,0.8528,0.6297,0.5250,0.4012,0.2901,0.2007,0.3356,0.4799,0.6147,0.6246,0.4973,0.3492,0.2662,0.3137,0.4282,0.4262,0.3511,0.2458,0.1259,0.0327,0.0181,0.0217,0.0038,0.0019,0.0065,0.0132,0.0108,0.0050,0.0085,0.0044,M\n",
      "\n",
      "0.0137,0.0297,0.0116,0.0082,0.0241,0.0253,0.0279,0.0130,0.0489,0.0874,0.1100,0.1084,0.1094,0.1023,0.0601,0.0906,0.1313,0.2758,0.3660,0.5269,0.5810,0.6181,0.5875,0.4639,0.5424,0.7367,0.9089,1.0000,0.8247,0.5441,0.3349,0.0877,0.1600,0.4169,0.6576,0.7390,0.7963,0.7493,0.6795,0.4713,0.2355,0.1704,0.2728,0.4016,0.4125,0.3470,0.2739,0.1790,0.0922,0.0276,0.0169,0.0081,0.0040,0.0025,0.0036,0.0058,0.0067,0.0035,0.0043,0.0033,M\n",
      "\n",
      "0.0015,0.0186,0.0289,0.0195,0.0515,0.0817,0.1005,0.0124,0.1168,0.1476,0.2118,0.2575,0.2354,0.1334,0.0092,0.1951,0.3685,0.4646,0.5418,0.6260,0.7420,0.8257,0.8609,0.8400,0.8949,0.9945,1.0000,0.9649,0.8747,0.6257,0.2184,0.2945,0.3645,0.5012,0.7843,0.9361,0.8195,0.6207,0.4513,0.3004,0.2674,0.2241,0.3141,0.3693,0.2986,0.2226,0.0849,0.0359,0.0289,0.0122,0.0045,0.0108,0.0075,0.0089,0.0036,0.0029,0.0013,0.0010,0.0032,0.0047,M\n",
      "\n",
      "0.0130,0.0120,0.0436,0.0624,0.0428,0.0349,0.0384,0.0446,0.1318,0.1375,0.2026,0.2389,0.2112,0.1444,0.0742,0.1533,0.3052,0.4116,0.5466,0.5933,0.6663,0.7333,0.7136,0.7014,0.7758,0.9137,0.9964,1.0000,0.8881,0.6585,0.2707,0.1746,0.2709,0.4853,0.7184,0.8209,0.7536,0.6496,0.4708,0.3482,0.3508,0.3181,0.3524,0.3659,0.2846,0.1714,0.0694,0.0303,0.0292,0.0116,0.0024,0.0084,0.0100,0.0018,0.0035,0.0058,0.0011,0.0009,0.0033,0.0026,M\n",
      "\n",
      "0.0134,0.0172,0.0178,0.0363,0.0444,0.0744,0.0800,0.0456,0.0368,0.1250,0.2405,0.2325,0.2523,0.1472,0.0669,0.1100,0.2353,0.3282,0.4416,0.5167,0.6508,0.7793,0.7978,0.7786,0.8587,0.9321,0.9454,0.8645,0.7220,0.4850,0.1357,0.2951,0.4715,0.6036,0.8083,0.9870,0.8800,0.6411,0.4276,0.2702,0.2642,0.3342,0.4335,0.4542,0.3960,0.2525,0.1084,0.0372,0.0286,0.0099,0.0046,0.0094,0.0048,0.0047,0.0016,0.0008,0.0042,0.0024,0.0027,0.0041,M\n",
      "\n",
      "0.0179,0.0136,0.0408,0.0633,0.0596,0.0808,0.2090,0.3465,0.5276,0.5965,0.6254,0.4507,0.3693,0.2864,0.1635,0.0422,0.1785,0.4394,0.6950,0.8097,0.8550,0.8717,0.8601,0.9201,0.8729,0.8084,0.8694,0.8411,0.5793,0.3754,0.3485,0.4639,0.6495,0.6901,0.5666,0.5188,0.5060,0.3885,0.3762,0.3738,0.2605,0.1591,0.1875,0.2267,0.1577,0.1211,0.0883,0.0850,0.0355,0.0219,0.0086,0.0123,0.0060,0.0187,0.0111,0.0126,0.0081,0.0155,0.0160,0.0085,M\n",
      "\n",
      "0.0180,0.0444,0.0476,0.0698,0.1615,0.0887,0.0596,0.1071,0.3175,0.2918,0.3273,0.3035,0.3033,0.2587,0.1682,0.1308,0.2803,0.4519,0.6641,0.7683,0.6960,0.4393,0.2432,0.2886,0.4974,0.8172,1.0000,0.9238,0.8519,0.7722,0.5772,0.5190,0.6824,0.6220,0.5054,0.3578,0.3809,0.3813,0.3359,0.2771,0.3648,0.3834,0.3453,0.2096,0.1031,0.0798,0.0701,0.0526,0.0241,0.0117,0.0122,0.0122,0.0114,0.0098,0.0027,0.0025,0.0026,0.0050,0.0073,0.0022,M\n",
      "\n",
      "0.0329,0.0216,0.0386,0.0627,0.1158,0.1482,0.2054,0.1605,0.2532,0.2672,0.3056,0.3161,0.2314,0.2067,0.1804,0.2808,0.4423,0.5947,0.6601,0.5844,0.4539,0.4789,0.5646,0.5281,0.7115,1.0000,0.9564,0.6090,0.5112,0.4000,0.0482,0.1852,0.2186,0.1436,0.1757,0.1428,0.1644,0.3089,0.3648,0.4441,0.3859,0.2813,0.1238,0.0953,0.1201,0.0825,0.0618,0.0141,0.0108,0.0124,0.0104,0.0095,0.0151,0.0059,0.0015,0.0053,0.0016,0.0042,0.0053,0.0074,M\n",
      "\n",
      "0.0191,0.0173,0.0291,0.0301,0.0463,0.0690,0.0576,0.1103,0.2423,0.3134,0.4786,0.5239,0.4393,0.3440,0.2869,0.3889,0.4420,0.3892,0.4088,0.5006,0.7271,0.9385,1.0000,0.9831,0.9932,0.9161,0.8237,0.6957,0.4536,0.3281,0.2522,0.3964,0.4154,0.3308,0.1445,0.1923,0.3208,0.3367,0.5683,0.5505,0.3231,0.0448,0.3131,0.3387,0.4130,0.3639,0.2069,0.0859,0.0600,0.0267,0.0125,0.0040,0.0136,0.0137,0.0172,0.0132,0.0110,0.0122,0.0114,0.0068,M\n",
      "\n",
      "0.0294,0.0123,0.0117,0.0113,0.0497,0.0998,0.1326,0.1117,0.2984,0.3473,0.4231,0.5044,0.5237,0.4398,0.3236,0.2956,0.3286,0.3231,0.4528,0.6339,0.7044,0.8314,0.8449,0.8512,0.9138,0.9985,1.0000,0.7544,0.4661,0.3924,0.3849,0.4674,0.4245,0.3095,0.0752,0.2885,0.4072,0.3170,0.2863,0.2634,0.0541,0.1874,0.3459,0.4646,0.4366,0.2581,0.1319,0.0505,0.0112,0.0059,0.0041,0.0056,0.0104,0.0079,0.0014,0.0054,0.0015,0.0006,0.0081,0.0043,M\n",
      "\n",
      "0.0635,0.0709,0.0453,0.0333,0.0185,0.1260,0.1015,0.1918,0.3362,0.3900,0.4674,0.5632,0.5506,0.4343,0.3052,0.3492,0.3975,0.3875,0.5280,0.7198,0.7702,0.8562,0.8688,0.9236,1.0000,0.9662,0.9822,0.7360,0.4158,0.2918,0.3280,0.3690,0.3450,0.2863,0.0864,0.3724,0.4649,0.3488,0.1817,0.1142,0.1220,0.2621,0.4461,0.4726,0.3263,0.1423,0.0390,0.0406,0.0311,0.0086,0.0154,0.0048,0.0025,0.0087,0.0072,0.0095,0.0086,0.0085,0.0040,0.0051,M\n",
      "\n",
      "0.0201,0.0165,0.0344,0.0330,0.0397,0.0443,0.0684,0.0903,0.1739,0.2571,0.2931,0.3108,0.3603,0.3002,0.2718,0.2007,0.1801,0.2234,0.3568,0.5492,0.7209,0.8318,0.8864,0.9520,0.9637,1.0000,0.9673,0.8664,0.7896,0.6345,0.5351,0.4056,0.2563,0.2894,0.3588,0.4296,0.4773,0.4516,0.3765,0.3051,0.1921,0.1184,0.1984,0.1570,0.0660,0.1294,0.0797,0.0052,0.0233,0.0152,0.0125,0.0054,0.0057,0.0137,0.0109,0.0035,0.0056,0.0105,0.0082,0.0036,M\n",
      "\n",
      "0.0197,0.0394,0.0384,0.0076,0.0251,0.0629,0.0747,0.0578,0.1357,0.1695,0.1734,0.2470,0.3141,0.3297,0.2759,0.2056,0.1162,0.1884,0.3390,0.3926,0.4282,0.5418,0.6448,0.7223,0.7853,0.7984,0.8847,0.9582,0.8990,0.6831,0.6108,0.5480,0.5058,0.4476,0.2401,0.1405,0.1772,0.1742,0.3326,0.4021,0.3009,0.2075,0.1206,0.0255,0.0298,0.0691,0.0781,0.0777,0.0369,0.0057,0.0091,0.0134,0.0097,0.0042,0.0058,0.0072,0.0041,0.0045,0.0047,0.0054,M\n",
      "\n",
      "0.0394,0.0420,0.0446,0.0551,0.0597,0.1416,0.0956,0.0802,0.1618,0.2558,0.3078,0.3404,0.3400,0.3951,0.3352,0.2252,0.2086,0.2248,0.3382,0.4578,0.6474,0.6708,0.7007,0.7619,0.7745,0.6767,0.7373,0.7834,0.9619,1.0000,0.8086,0.5558,0.5409,0.4988,0.3108,0.2897,0.2244,0.0960,0.2287,0.3228,0.3454,0.3882,0.3240,0.0926,0.1173,0.0566,0.0766,0.0969,0.0588,0.0050,0.0118,0.0146,0.0040,0.0114,0.0032,0.0062,0.0101,0.0068,0.0053,0.0087,M\n",
      "\n",
      "0.0310,0.0221,0.0433,0.0191,0.0964,0.1827,0.1106,0.1702,0.2804,0.4432,0.5222,0.5611,0.5379,0.4048,0.2245,0.1784,0.2297,0.2720,0.5209,0.6898,0.8202,0.8780,0.7600,0.7616,0.7152,0.7288,0.8686,0.9509,0.8348,0.5730,0.4363,0.4289,0.4240,0.3156,0.1287,0.1477,0.2062,0.2400,0.5173,0.5168,0.1491,0.2407,0.3415,0.4494,0.4624,0.2001,0.0775,0.1232,0.0783,0.0089,0.0249,0.0204,0.0059,0.0053,0.0079,0.0037,0.0015,0.0056,0.0067,0.0054,M\n",
      "\n",
      "0.0423,0.0321,0.0709,0.0108,0.1070,0.0973,0.0961,0.1323,0.2462,0.2696,0.3412,0.4292,0.3682,0.3940,0.2965,0.3172,0.2825,0.3050,0.2408,0.5420,0.6802,0.6320,0.5824,0.6805,0.5984,0.8412,0.9911,0.9187,0.8005,0.6713,0.5632,0.7332,0.6038,0.2575,0.0349,0.1799,0.3039,0.4760,0.5756,0.4254,0.5046,0.7179,0.6163,0.5663,0.5749,0.3593,0.2526,0.2299,0.1271,0.0356,0.0367,0.0176,0.0035,0.0093,0.0121,0.0075,0.0056,0.0021,0.0043,0.0017,M\n",
      "\n",
      "0.0095,0.0308,0.0539,0.0411,0.0613,0.1039,0.1016,0.1394,0.2592,0.3745,0.4229,0.4499,0.5404,0.4303,0.3333,0.3496,0.3426,0.2851,0.4062,0.6833,0.7650,0.6670,0.5703,0.5995,0.6484,0.8614,0.9819,0.9380,0.8435,0.6074,0.5403,0.6890,0.5977,0.3244,0.0516,0.3157,0.3590,0.3881,0.5716,0.4314,0.3051,0.4393,0.4302,0.4831,0.5084,0.1952,0.1539,0.2037,0.1054,0.0251,0.0357,0.0181,0.0019,0.0102,0.0133,0.0040,0.0042,0.0030,0.0031,0.0033,M\n",
      "\n",
      "0.0096,0.0404,0.0682,0.0688,0.0887,0.0932,0.0955,0.2140,0.2546,0.2952,0.4025,0.5148,0.4901,0.4127,0.3575,0.3447,0.3068,0.2945,0.4351,0.7264,0.8147,0.8103,0.6665,0.6958,0.7748,0.8688,1.0000,0.9941,0.8793,0.6482,0.5876,0.6408,0.4972,0.2755,0.0300,0.3356,0.3167,0.4133,0.6281,0.4977,0.2613,0.4697,0.4806,0.4921,0.5294,0.2216,0.1401,0.1888,0.0947,0.0134,0.0310,0.0237,0.0078,0.0144,0.0170,0.0012,0.0109,0.0036,0.0043,0.0018,M\n",
      "\n",
      "0.0269,0.0383,0.0505,0.0707,0.1313,0.2103,0.2263,0.2524,0.3595,0.5915,0.6675,0.5679,0.5175,0.3334,0.2002,0.2856,0.2937,0.3424,0.5949,0.7526,0.8959,0.8147,0.7109,0.7378,0.7201,0.8254,0.8917,0.9820,0.8179,0.4848,0.3203,0.2775,0.2382,0.2911,0.1675,0.3156,0.1869,0.3391,0.5993,0.4124,0.1181,0.3651,0.4655,0.4777,0.3517,0.0920,0.1227,0.1785,0.1085,0.0300,0.0346,0.0167,0.0199,0.0145,0.0081,0.0045,0.0043,0.0027,0.0055,0.0057,M\n",
      "\n",
      "0.0340,0.0625,0.0381,0.0257,0.0441,0.1027,0.1287,0.1850,0.2647,0.4117,0.5245,0.5341,0.5554,0.3915,0.2950,0.3075,0.3021,0.2719,0.5443,0.7932,0.8751,0.8667,0.7107,0.6911,0.7287,0.8792,1.0000,0.9816,0.8984,0.6048,0.4934,0.5371,0.4586,0.2908,0.0774,0.2249,0.1602,0.3958,0.6117,0.5196,0.2321,0.4370,0.3797,0.4322,0.4892,0.1901,0.0940,0.1364,0.0906,0.0144,0.0329,0.0141,0.0019,0.0067,0.0099,0.0042,0.0057,0.0051,0.0033,0.0058,M\n",
      "\n",
      "0.0209,0.0191,0.0411,0.0321,0.0698,0.1579,0.1438,0.1402,0.3048,0.3914,0.3504,0.3669,0.3943,0.3311,0.3331,0.3002,0.2324,0.1381,0.3450,0.4428,0.4890,0.3677,0.4379,0.4864,0.6207,0.7256,0.6624,0.7689,0.7981,0.8577,0.9273,0.7009,0.4851,0.3409,0.1406,0.1147,0.1433,0.1820,0.3605,0.5529,0.5988,0.5077,0.5512,0.5027,0.7034,0.5904,0.4069,0.2761,0.1584,0.0510,0.0054,0.0078,0.0201,0.0104,0.0039,0.0031,0.0062,0.0087,0.0070,0.0042,M\n",
      "\n",
      "0.0368,0.0279,0.0103,0.0566,0.0759,0.0679,0.0970,0.1473,0.2164,0.2544,0.2936,0.2935,0.2657,0.3187,0.2794,0.2534,0.1980,0.1929,0.2826,0.3245,0.3504,0.3324,0.4217,0.4774,0.4808,0.6325,0.8334,0.9458,1.0000,0.8425,0.5524,0.4795,0.5200,0.3968,0.1940,0.1519,0.2010,0.1736,0.1029,0.2244,0.3717,0.4449,0.3939,0.2030,0.2010,0.2187,0.1840,0.1477,0.0971,0.0224,0.0151,0.0105,0.0024,0.0018,0.0057,0.0092,0.0009,0.0086,0.0110,0.0052,M\n",
      "\n",
      "0.0089,0.0274,0.0248,0.0237,0.0224,0.0845,0.1488,0.1224,0.1569,0.2119,0.3003,0.3094,0.2743,0.2547,0.1870,0.1452,0.1457,0.2429,0.3259,0.3679,0.3355,0.3100,0.3914,0.5280,0.6409,0.7707,0.8754,1.0000,0.9806,0.6969,0.4973,0.5020,0.5359,0.3842,0.1848,0.1149,0.1570,0.1311,0.1583,0.2631,0.3103,0.4512,0.3785,0.1269,0.1459,0.1092,0.1485,0.1385,0.0716,0.0176,0.0199,0.0096,0.0103,0.0093,0.0025,0.0044,0.0021,0.0069,0.0060,0.0018,M\n",
      "\n",
      "0.0158,0.0239,0.0150,0.0494,0.0988,0.1425,0.1463,0.1219,0.1697,0.1923,0.2361,0.2719,0.3049,0.2986,0.2226,0.1745,0.2459,0.3100,0.3572,0.4283,0.4268,0.3735,0.4585,0.6094,0.7221,0.7595,0.8706,1.0000,0.9815,0.7187,0.5848,0.4192,0.3756,0.3263,0.1944,0.1394,0.1670,0.1275,0.1666,0.2574,0.2258,0.2777,0.1613,0.1335,0.1976,0.1234,0.1554,0.1057,0.0490,0.0097,0.0223,0.0121,0.0108,0.0057,0.0028,0.0079,0.0034,0.0046,0.0022,0.0021,M\n",
      "\n",
      "0.0156,0.0210,0.0282,0.0596,0.0462,0.0779,0.1365,0.0780,0.1038,0.1567,0.2476,0.2783,0.2896,0.2956,0.3189,0.1892,0.1730,0.2226,0.2427,0.3149,0.4102,0.3808,0.4896,0.6292,0.7519,0.7985,0.8830,0.9915,0.9223,0.6981,0.6167,0.5069,0.3921,0.3524,0.2183,0.1245,0.1592,0.1626,0.2356,0.2483,0.2437,0.2715,0.1184,0.1157,0.1449,0.1883,0.1954,0.1492,0.0511,0.0155,0.0189,0.0150,0.0060,0.0082,0.0091,0.0038,0.0056,0.0056,0.0048,0.0024,M\n",
      "\n",
      "0.0315,0.0252,0.0167,0.0479,0.0902,0.1057,0.1024,0.1209,0.1241,0.1533,0.2128,0.2536,0.2686,0.2803,0.1886,0.1485,0.2160,0.2417,0.2989,0.3341,0.3786,0.3956,0.5232,0.6913,0.7868,0.8337,0.9199,1.0000,0.8990,0.6456,0.5967,0.4355,0.2997,0.2294,0.1866,0.0922,0.1829,0.1743,0.2452,0.2407,0.2518,0.3184,0.1685,0.0675,0.1186,0.1833,0.1878,0.1114,0.0310,0.0143,0.0138,0.0108,0.0062,0.0044,0.0072,0.0007,0.0054,0.0035,0.0001,0.0055,M\n",
      "\n",
      "0.0056,0.0267,0.0221,0.0561,0.0936,0.1146,0.0706,0.0996,0.1673,0.1859,0.2481,0.2712,0.2934,0.2637,0.1880,0.1405,0.2028,0.2613,0.2778,0.3346,0.3830,0.4003,0.5114,0.6860,0.7490,0.7843,0.9021,1.0000,0.8888,0.6511,0.6083,0.4463,0.2948,0.1729,0.1488,0.0801,0.1770,0.1382,0.2404,0.2046,0.1970,0.2778,0.1377,0.0685,0.0664,0.1665,0.1807,0.1245,0.0516,0.0044,0.0185,0.0072,0.0055,0.0074,0.0068,0.0084,0.0037,0.0024,0.0034,0.0007,M\n",
      "\n",
      "0.0203,0.0121,0.0380,0.0128,0.0537,0.0874,0.1021,0.0852,0.1136,0.1747,0.2198,0.2721,0.2105,0.1727,0.2040,0.1786,0.1318,0.2260,0.2358,0.3107,0.3906,0.3631,0.4809,0.6531,0.7812,0.8395,0.9180,0.9769,0.8937,0.7022,0.6500,0.5069,0.3903,0.3009,0.1565,0.0985,0.2200,0.2243,0.2736,0.2152,0.2438,0.3154,0.2112,0.0991,0.0594,0.1940,0.1937,0.1082,0.0336,0.0177,0.0209,0.0134,0.0094,0.0047,0.0045,0.0042,0.0028,0.0036,0.0013,0.0016,M\n",
      "\n",
      "0.0392,0.0108,0.0267,0.0257,0.0410,0.0491,0.1053,0.1690,0.2105,0.2471,0.2680,0.3049,0.2863,0.2294,0.1165,0.2127,0.2062,0.2222,0.3241,0.4330,0.5071,0.5944,0.7078,0.7641,0.8878,0.9711,0.9880,0.9812,0.9464,0.8542,0.6457,0.3397,0.3828,0.3204,0.1331,0.0440,0.1234,0.2030,0.1652,0.1043,0.1066,0.2110,0.2417,0.1631,0.0769,0.0723,0.0912,0.0812,0.0496,0.0101,0.0089,0.0083,0.0080,0.0026,0.0079,0.0042,0.0071,0.0044,0.0022,0.0014,M\n",
      "\n",
      "0.0129,0.0141,0.0309,0.0375,0.0767,0.0787,0.0662,0.1108,0.1777,0.2245,0.2431,0.3134,0.3206,0.2917,0.2249,0.2347,0.2143,0.2939,0.4898,0.6127,0.7531,0.7718,0.7432,0.8673,0.9308,0.9836,1.0000,0.9595,0.8722,0.6862,0.4901,0.3280,0.3115,0.1969,0.1019,0.0317,0.0756,0.0907,0.1066,0.1380,0.0665,0.1475,0.2470,0.2788,0.2709,0.2283,0.1818,0.1185,0.0546,0.0219,0.0204,0.0124,0.0093,0.0072,0.0019,0.0027,0.0054,0.0017,0.0024,0.0029,M\n",
      "\n",
      "0.0050,0.0017,0.0270,0.0450,0.0958,0.0830,0.0879,0.1220,0.1977,0.2282,0.2521,0.3484,0.3309,0.2614,0.1782,0.2055,0.2298,0.3545,0.6218,0.7265,0.8346,0.8268,0.8366,0.9408,0.9510,0.9801,0.9974,1.0000,0.9036,0.6409,0.3857,0.2908,0.2040,0.1653,0.1769,0.1140,0.0740,0.0941,0.0621,0.0426,0.0572,0.1068,0.1909,0.2229,0.2203,0.2265,0.1766,0.1097,0.0558,0.0142,0.0281,0.0165,0.0056,0.0010,0.0027,0.0062,0.0024,0.0063,0.0017,0.0028,M\n",
      "\n",
      "0.0366,0.0421,0.0504,0.0250,0.0596,0.0252,0.0958,0.0991,0.1419,0.1847,0.2222,0.2648,0.2508,0.2291,0.1555,0.1863,0.2387,0.3345,0.5233,0.6684,0.7766,0.7928,0.7940,0.9129,0.9498,0.9835,1.0000,0.9471,0.8237,0.6252,0.4181,0.3209,0.2658,0.2196,0.1588,0.0561,0.0948,0.1700,0.1215,0.1282,0.0386,0.1329,0.2331,0.2468,0.1960,0.1985,0.1570,0.0921,0.0549,0.0194,0.0166,0.0132,0.0027,0.0022,0.0059,0.0016,0.0025,0.0017,0.0027,0.0027,M\n",
      "\n",
      "0.0238,0.0318,0.0422,0.0399,0.0788,0.0766,0.0881,0.1143,0.1594,0.2048,0.2652,0.3100,0.2381,0.1918,0.1430,0.1735,0.1781,0.2852,0.5036,0.6166,0.7616,0.8125,0.7793,0.8788,0.8813,0.9470,1.0000,0.9739,0.8446,0.6151,0.4302,0.3165,0.2869,0.2017,0.1206,0.0271,0.0580,0.1262,0.1072,0.1082,0.0360,0.1197,0.2061,0.2054,0.1878,0.2047,0.1716,0.1069,0.0477,0.0170,0.0186,0.0096,0.0071,0.0084,0.0038,0.0026,0.0028,0.0013,0.0035,0.0060,M\n",
      "\n",
      "0.0116,0.0744,0.0367,0.0225,0.0076,0.0545,0.1110,0.1069,0.1708,0.2271,0.3171,0.2882,0.2657,0.2307,0.1889,0.1791,0.2298,0.3715,0.6223,0.7260,0.7934,0.8045,0.8067,0.9173,0.9327,0.9562,1.0000,0.9818,0.8684,0.6381,0.3997,0.3242,0.2835,0.2413,0.2321,0.1260,0.0693,0.0701,0.1439,0.1475,0.0438,0.0469,0.1476,0.1742,0.1555,0.1651,0.1181,0.0720,0.0321,0.0056,0.0202,0.0141,0.0103,0.0100,0.0034,0.0026,0.0037,0.0044,0.0057,0.0035,M\n",
      "\n",
      "0.0131,0.0387,0.0329,0.0078,0.0721,0.1341,0.1626,0.1902,0.2610,0.3193,0.3468,0.3738,0.3055,0.1926,0.1385,0.2122,0.2758,0.4576,0.6487,0.7154,0.8010,0.7924,0.8793,1.0000,0.9865,0.9474,0.9474,0.9315,0.8326,0.6213,0.3772,0.2822,0.2042,0.2190,0.2223,0.1327,0.0521,0.0618,0.1416,0.1460,0.0846,0.1055,0.1639,0.1916,0.2085,0.2335,0.1964,0.1300,0.0633,0.0183,0.0137,0.0150,0.0076,0.0032,0.0037,0.0071,0.0040,0.0009,0.0015,0.0085,M\n",
      "\n",
      "0.0335,0.0258,0.0398,0.0570,0.0529,0.1091,0.1709,0.1684,0.1865,0.2660,0.3188,0.3553,0.3116,0.1965,0.1780,0.2794,0.2870,0.3969,0.5599,0.6936,0.7969,0.7452,0.8203,0.9261,0.8810,0.8814,0.9301,0.9955,0.8576,0.6069,0.3934,0.2464,0.1645,0.1140,0.0956,0.0080,0.0702,0.0936,0.0894,0.1127,0.0873,0.1020,0.1964,0.2256,0.1814,0.2012,0.1688,0.1037,0.0501,0.0136,0.0130,0.0120,0.0039,0.0053,0.0062,0.0046,0.0045,0.0022,0.0005,0.0031,M\n",
      "\n",
      "0.0272,0.0378,0.0488,0.0848,0.1127,0.1103,0.1349,0.2337,0.3113,0.3997,0.3941,0.3309,0.2926,0.1760,0.1739,0.2043,0.2088,0.2678,0.2434,0.1839,0.2802,0.6172,0.8015,0.8313,0.8440,0.8494,0.9168,1.0000,0.7896,0.5371,0.6472,0.6505,0.4959,0.2175,0.0990,0.0434,0.1708,0.1979,0.1880,0.1108,0.1702,0.0585,0.0638,0.1391,0.0638,0.0581,0.0641,0.1044,0.0732,0.0275,0.0146,0.0091,0.0045,0.0043,0.0043,0.0098,0.0054,0.0051,0.0065,0.0103,M\n",
      "\n",
      "0.0187,0.0346,0.0168,0.0177,0.0393,0.1630,0.2028,0.1694,0.2328,0.2684,0.3108,0.2933,0.2275,0.0994,0.1801,0.2200,0.2732,0.2862,0.2034,0.1740,0.4130,0.6879,0.8120,0.8453,0.8919,0.9300,0.9987,1.0000,0.8104,0.6199,0.6041,0.5547,0.4160,0.1472,0.0849,0.0608,0.0969,0.1411,0.1676,0.1200,0.1201,0.1036,0.1977,0.1339,0.0902,0.1085,0.1521,0.1363,0.0858,0.0290,0.0203,0.0116,0.0098,0.0199,0.0033,0.0101,0.0065,0.0115,0.0193,0.0157,M\n",
      "\n",
      "0.0323,0.0101,0.0298,0.0564,0.0760,0.0958,0.0990,0.1018,0.1030,0.2154,0.3085,0.3425,0.2990,0.1402,0.1235,0.1534,0.1901,0.2429,0.2120,0.2395,0.3272,0.5949,0.8302,0.9045,0.9888,0.9912,0.9448,1.0000,0.9092,0.7412,0.7691,0.7117,0.5304,0.2131,0.0928,0.1297,0.1159,0.1226,0.1768,0.0345,0.1562,0.0824,0.1149,0.1694,0.0954,0.0080,0.0790,0.1255,0.0647,0.0179,0.0051,0.0061,0.0093,0.0135,0.0063,0.0063,0.0034,0.0032,0.0062,0.0067,M\n",
      "\n",
      "0.0522,0.0437,0.0180,0.0292,0.0351,0.1171,0.1257,0.1178,0.1258,0.2529,0.2716,0.2374,0.1878,0.0983,0.0683,0.1503,0.1723,0.2339,0.1962,0.1395,0.3164,0.5888,0.7631,0.8473,0.9424,0.9986,0.9699,1.0000,0.8630,0.6979,0.7717,0.7305,0.5197,0.1786,0.1098,0.1446,0.1066,0.1440,0.1929,0.0325,0.1490,0.0328,0.0537,0.1309,0.0910,0.0757,0.1059,0.1005,0.0535,0.0235,0.0155,0.0160,0.0029,0.0051,0.0062,0.0089,0.0140,0.0138,0.0077,0.0031,M\n",
      "\n",
      "0.0303,0.0353,0.0490,0.0608,0.0167,0.1354,0.1465,0.1123,0.1945,0.2354,0.2898,0.2812,0.1578,0.0273,0.0673,0.1444,0.2070,0.2645,0.2828,0.4293,0.5685,0.6990,0.7246,0.7622,0.9242,1.0000,0.9979,0.8297,0.7032,0.7141,0.6893,0.4961,0.2584,0.0969,0.0776,0.0364,0.1572,0.1823,0.1349,0.0849,0.0492,0.1367,0.1552,0.1548,0.1319,0.0985,0.1258,0.0954,0.0489,0.0241,0.0042,0.0086,0.0046,0.0126,0.0036,0.0035,0.0034,0.0079,0.0036,0.0048,M\n",
      "\n",
      "0.0260,0.0363,0.0136,0.0272,0.0214,0.0338,0.0655,0.1400,0.1843,0.2354,0.2720,0.2442,0.1665,0.0336,0.1302,0.1708,0.2177,0.3175,0.3714,0.4552,0.5700,0.7397,0.8062,0.8837,0.9432,1.0000,0.9375,0.7603,0.7123,0.8358,0.7622,0.4567,0.1715,0.1549,0.1641,0.1869,0.2655,0.1713,0.0959,0.0768,0.0847,0.2076,0.2505,0.1862,0.1439,0.1470,0.0991,0.0041,0.0154,0.0116,0.0181,0.0146,0.0129,0.0047,0.0039,0.0061,0.0040,0.0036,0.0061,0.0115,M\n",
      "\n"
     ]
    }
   ],
   "source": [
    "__author__ = 'mike-bowles'\n",
    "import urllib.request, urllib.error, urllib.parse\n",
    "target_url = \"https://archive.ics.uci.edu/ml/machine-learning-databases/undocumented/connectionist-bench/sonar/sonar.all-data\"\n",
    "\n",
    "\n",
    "for line in urllib.request.urlopen(target_url):\n",
    "    print(line.decode())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### regressionErrorMeasures.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Errors \n",
      "[1.0, 0.6000000000000001, 1.1999999999999997, -2.5, -2.4, 1.25]\n",
      "Squared Error\n",
      "[1.0, 0.3600000000000001, 1.4399999999999993, 6.25, 5.76, 1.5625]\n",
      "Absolute Value of Error\n",
      "[1.0, 0.6000000000000001, 1.1999999999999997, 2.5, 2.4, 1.25]\n",
      "MSE =  2.72875\n",
      "RMSE =  1.651892853668179\n",
      "MAE =  1.4916666666666665\n",
      "Target Variance =  7.570347222222222\n",
      "Target Standard Deviation =  2.7514263977475797\n"
     ]
    }
   ],
   "source": [
    "__author__ = 'mike-bowles'\n",
    "\n",
    "\n",
    "#here are some made-up numbers to start with\n",
    "target = [1.5, 2.1, 3.3, -4.7, -2.3, 0.75]\n",
    "prediction = [0.5, 1.5, 2.1, -2.2, 0.1, -0.5]\n",
    "\n",
    "error = []\n",
    "for i in range(len(target)):\n",
    "    error.append(target[i] - prediction[i])\n",
    "\n",
    "#print the errors\n",
    "print(\"Errors \",)\n",
    "print(error)\n",
    "#ans:  [1.0, 0.60000000000000009, 1.1999999999999997, -2.5, -2.3999999999999999, 1.25]\n",
    "\n",
    "\n",
    "\n",
    "#calculate the squared errors and absolute value of errors\n",
    "squaredError = []\n",
    "absError = []\n",
    "for val in error:\n",
    "    squaredError.append(val*val)\n",
    "    absError.append(abs(val))\n",
    "\n",
    "\n",
    "#print squared errors and absolute value of errors\n",
    "print(\"Squared Error\")\n",
    "print(squaredError)\n",
    "#ans: [1.0, 0.3600000000000001, 1.4399999999999993, 6.25, 5.7599999999999998, 1.5625]\n",
    "print(\"Absolute Value of Error\")\n",
    "print(absError)\n",
    "#ans: [1.0, 0.60000000000000009, 1.1999999999999997, 2.5, 2.3999999999999999, 1.25]\n",
    "\n",
    "\n",
    "#calculate and print mean squared error MSE\n",
    "print(\"MSE = \", sum(squaredError)/len(squaredError))\n",
    "#ans: 2.72875\n",
    "\n",
    "\n",
    "from math import sqrt\n",
    "#calculate and print square root of MSE (RMSE)\n",
    "print(\"RMSE = \", sqrt(sum(squaredError)/len(squaredError)))\n",
    "#ans: 1.65189285367\n",
    "\n",
    "\n",
    "#calculate and print mean absolute error MAE\n",
    "print(\"MAE = \", sum(absError)/len(absError))\n",
    "#ans: 1.49166666667\n",
    "\n",
    "\n",
    "#compare MSE to target variance\n",
    "targetDeviation = []\n",
    "targetMean = sum(target)/len(target)\n",
    "for val in target:\n",
    "    targetDeviation.append((val - targetMean)*(val - targetMean))\n",
    "\n",
    "#print the target variance\n",
    "print(\"Target Variance = \", sum(targetDeviation)/len(targetDeviation))\n",
    "#ans: 7.5703472222222219\n",
    "\n",
    "#print the the target standard deviation (square root of variance)\n",
    "print(\"Target Standard Deviation = \", sqrt(sum(targetDeviation)/len(targetDeviation)))\n",
    "#ans: 2.7514263977475797"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ridgeWine.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMS Error             alpha\n",
      "0.659578817634 1.0\n",
      "0.657861091881 0.1\n",
      "0.657617214464 0.010000000000000002\n",
      "0.657521648264 0.0010000000000000002\n",
      "0.657419068011 0.00010000000000000002\n",
      "0.657394162885 1.0000000000000003e-05\n",
      "0.657391308716 1.0000000000000004e-06\n"
     ]
    },
    {
     "data": {
      "image/png": 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f26d37977BM6e+eOOOy7Dys2y54BpAAeMFYsI3nvvvf3Odl577TU+/vjjvf36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\noyaOYwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f322c5fee10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f322c5ed438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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OVj1BFWuEw1XDahMa6kOk7wPOCt2QBNhaS1SlC0pQJSp4HwEDAm0f6DpP03ui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\nDGNGMIVvGIYxI/x/CtACTEvobNAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f321d634080>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "__author__ = 'mike-bowles'\n",
    "\n",
    "import urllib.request, urllib.error, urllib.parse\n",
    "import numpy\n",
    "from sklearn import datasets, linear_model\n",
    "from math import sqrt\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "#read data into iterable\n",
    "target_url = \"http://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-red.csv\"\n",
    "data = urllib.request.urlopen(target_url)\n",
    "\n",
    "xList = []\n",
    "labels = []\n",
    "names = []\n",
    "firstLine = True\n",
    "for line in data:\n",
    "    if firstLine:\n",
    "        names = line.strip().decode().split(\";\")\n",
    "        firstLine = False\n",
    "    else:\n",
    "        #split on semi-colon\n",
    "        row = line.strip().decode().split(\";\")\n",
    "        #put labels in separate array\n",
    "        labels.append(float(row[-1]))\n",
    "        #remove label from row\n",
    "        row.pop()\n",
    "        #convert row to floats\n",
    "        floatRow = [float(num) for num in row]\n",
    "        xList.append(floatRow)\n",
    "\n",
    "#divide attributes and labels into training and test sets\n",
    "indices = range(len(xList))\n",
    "xListTest = [xList[i] for i in indices if i%3 == 0 ]\n",
    "xListTrain = [xList[i] for i in indices if i%3 != 0 ]\n",
    "labelsTest = [labels[i] for i in indices if i%3 == 0]\n",
    "labelsTrain = [labels[i] for i in indices if i%3 != 0]\n",
    "\n",
    "xTrain = numpy.array(xListTrain); yTrain = numpy.array(labelsTrain); xTest = numpy.array(xListTest); yTest = numpy.array(labelsTest)\n",
    "\n",
    "alphaList = [0.1**i for i in [0,1, 2, 3, 4, 5, 6]]\n",
    "\n",
    "rmsError = []\n",
    "for alph in alphaList:\n",
    "    wineRidgeModel = linear_model.Ridge(alpha=alph)\n",
    "    wineRidgeModel.fit(xTrain, yTrain)\n",
    "    rmsError.append(numpy.linalg.norm((yTest-wineRidgeModel.predict(xTest)), 2)/sqrt(len(yTest)))\n",
    "\n",
    "print(\"RMS Error             alpha\")\n",
    "for i in range(len(rmsError)):\n",
    "    print(rmsError[i], alphaList[i])\n",
    "\n",
    "#plot curve of out-of-sample error versus alpha\n",
    "x = range(len(rmsError))\n",
    "plt.plot(x, rmsError, 'k')\n",
    "plt.xlabel('-log(alpha)')\n",
    "plt.ylabel('Error (RMS)')\n",
    "plt.show()\n",
    "\n",
    "#Plot histogram of out of sample errors for best alpha value and scatter plot of actual versus predicted\n",
    "#Identify index corresponding to min value, retrain with the corresponding value of alpha\n",
    "#Use resulting model to predict against out of sample data.  Plot errors (aka residuals)\n",
    "indexBest = rmsError.index(min(rmsError))\n",
    "alph = alphaList[indexBest]\n",
    "wineRidgeModel = linear_model.Ridge(alpha=alph)\n",
    "wineRidgeModel.fit(xTrain, yTrain)\n",
    "errorVector = yTest-wineRidgeModel.predict(xTest)\n",
    "plt.hist(errorVector)\n",
    "plt.xlabel(\"Bin Boundaries\")\n",
    "plt.ylabel(\"Counts\")\n",
    "plt.show()\n",
    "\n",
    "plt.scatter(wineRidgeModel.predict(xTest), yTest, s=100, alpha=0.10)\n",
    "plt.xlabel('Predicted Taste Score')\n",
    "plt.ylabel('Actual Taste Score')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### scatter_demo.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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g2zb4r//y60vffz9cfHHz3uu99/zuNxMmwMiRg8/v3++b+6JFpZfNffZZn9YLjRoFkyc3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\nCOAW4KutKiiSJD8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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f322c56f748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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B0hj2cvZqnCuLnHc5mszxjZd7sWxJa83igf1mYnYJyKUL/vDlXvqnMmX9ve2q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\nc3zYAJSzAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f321ef00da0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#!/usr/bin/env python\n",
    "from pylab import *\n",
    "\n",
    "N = 30\n",
    "x = 0.9*rand(N)\n",
    "y = 0.9*rand(N)\n",
    "area = pi*(10 * rand(N))**2 # 0 to 10 point radiuses\n",
    "scatter(x,y,s=area, marker='^', c='r')\n",
    "\n",
    "show()\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "N = 50\n",
    "x = np.random.rand(N)\n",
    "y = np.random.rand(N)\n",
    "area = np.pi * (15 * np.random.rand(N))**2 # 0 to 15 point radiuses\n",
    "\n",
    "plt.scatter(x, y, s=area, alpha=0.5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   },
   "outputs": [],
   "source": []
  }
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